diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/broadcast.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/broadcast.cpp index a22f29bba6c..cd5f2bae07f 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/broadcast.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/broadcast.cpp @@ -117,8 +117,6 @@ protected: } functionParams.front()->set_friendly_name("data"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(functionParams)); - std::shared_ptr broadcastOp; if (mode == ov::op::BroadcastType::EXPLICIT) { std::shared_ptr targetShapeOp; @@ -133,19 +131,19 @@ protected: } else { axesMappingOp = functionParams.size() > 2 ? functionParams[2] : functionParams[1]; } - broadcastOp = std::make_shared(paramOuts[0], + broadcastOp = std::make_shared(functionParams[0], targetShapeOp, axesMappingOp, mode); } else if (mode == ov::op::BroadcastType::NUMPY) { if (isTargetShapeConst) { auto targetShapeConst = ov::op::v0::Constant::create(ov::element::i64, {targetShapeRank}, targetShape); - broadcastOp = std::make_shared(paramOuts[0], + broadcastOp = std::make_shared(functionParams[0], targetShapeConst, mode); } else { - broadcastOp = std::make_shared(paramOuts[0], - paramOuts[1], + broadcastOp = std::make_shared(functionParams[0], + functionParams[1], mode); } } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/mvn.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/mvn.cpp index c9234bfd32b..b2b82043c30 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/mvn.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/mvn.cpp @@ -100,14 +100,12 @@ void MvnLayerCPUTest::SetUp() { init_input_shapes({inputShapes}); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netPrecision, shape)); - } - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto mvn = ngraph::builder::makeMVN(paramOuts[0], acrossChanels, normalizeVariance, eps); + + auto mvn = ngraph::builder::makeMVN(params[0], acrossChanels, normalizeVariance, eps); if (!axes.empty()) { - mvn = ngraph::builder::makeMVN(paramOuts[0], axes, normalizeVariance, eps); + mvn = ngraph::builder::makeMVN(params[0], axes, normalizeVariance, eps); } rel_threshold = 0.015f; diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/reduce.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/reduce.cpp index 95c23f98399..49be2dc0e41 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/reduce.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/reduce.cpp @@ -95,11 +95,8 @@ void ReduceCPULayerTest::SetUp() { init_input_shapes(inputShapes); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netPrecision, shape)); - } - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector shapeAxes; switch (opType) { @@ -116,7 +113,7 @@ void ReduceCPULayerTest::SetUp() { auto reductionAxesNode = std::dynamic_pointer_cast( std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape(shapeAxes), axes)); - const auto reduce = ngraph::builder::makeReduce(paramOuts[0], reductionAxesNode, keepDims, reductionType); + const auto reduce = ngraph::builder::makeReduce(params[0], reductionAxesNode, keepDims, reductionType); // hybrid layouts if (inFmts.size() != 0 && outFmts.size() == 0) { diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp index ac8a7149f88..59b3fc7990a 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp @@ -53,13 +53,10 @@ void SoftMaxLayerCPUTest::SetUp() { selectedType = makeSelectedTypeStr(selectedType, inType); init_input_shapes({config.inputShape}); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(inType, shape)); - } - const auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - const auto softMax = std::make_shared(paramOuts.at(0), config.axis); + const auto softMax = std::make_shared(params.at(0), config.axis); function = makeNgraphFunction(inType, params, softMax, "SoftMax"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/convolution.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/convolution.cpp index a7a863b5782..f713112cfc7 100755 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/convolution.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/convolution.cpp @@ -200,12 +200,9 @@ protected: std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType) = convParams; ov::ParameterVector inputParams; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) inputParams.push_back(std::make_shared(ov::element::f32, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); - - auto convolutionNode = ngraph::builder::makeConvolution(paramOuts.front(), netType, kernel, stride, padBegin, + auto convolutionNode = ngraph::builder::makeConvolution(inputParams[0], netType, kernel, stride, padBegin, padEnd, dilation, padType, convOutChannels); function = makeNgraphFunction(netType, inputParams, convolutionNode, "Convolution"); diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/fake_quantize.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/fake_quantize.cpp index e82f26d774a..a3d96b81acb 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/fake_quantize.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/fake_quantize.cpp @@ -112,16 +112,14 @@ protected: auto ngInPrec = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(inPrec); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(ngInPrec, shape)); - } - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); auto il = builder::makeConstant(ngInPrec, ranges[0], rangesBounds[0], rangesBounds[0].empty()); auto ih = builder::makeConstant(ngInPrec, ranges[1], rangesBounds[1], rangesBounds[1].empty()); auto ol = builder::makeConstant(ngInPrec, ranges[2], rangesBounds[2], rangesBounds[2].empty()); auto oh = builder::makeConstant(ngInPrec, ranges[3], rangesBounds[3], rangesBounds[3].empty()); - auto fq = std::make_shared(paramOuts[0], il, ih, ol, oh, levels); + auto fq = std::make_shared(params[0], il, ih, ol, oh, levels); layerName = shouldBeDecomposed ? "" : "FakeQuantize"; diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/gather.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/gather.cpp index 480247b44ea..9a171663653 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/gather.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/gather.cpp @@ -105,13 +105,12 @@ protected: params.push_back(std::make_shared(intInputsPrecision, inputDynamicShapes[2])); params[2]->set_friendly_name("axis"); } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::shared_ptr gatherNode; if (isAxisConstant) { - gatherNode = std::make_shared(paramOuts[0], paramOuts[1], + gatherNode = std::make_shared(params[0], params[1], ov::op::v0::Constant::create(intInputsPrecision, ov::Shape({1}), { axis }), batchDims); } else { - gatherNode = std::make_shared(paramOuts[0], paramOuts[1], paramOuts[2], batchDims); + gatherNode = std::make_shared(params[0], params[1], params[2], batchDims); } function = makeNgraphFunction(netPrecision, params, gatherNode, "GatherCPU"); @@ -205,8 +204,7 @@ protected: std::make_shared(netPrecision, inputDynamicShapes[0]) }; params[0]->set_friendly_name("data"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - std::shared_ptr gatherNode = std::make_shared(paramOuts[0], + std::shared_ptr gatherNode = std::make_shared(params[0], ov::op::v0::Constant::create(intInputsPrecision, ov::Shape({indices.size()}), indices), ov::op::v0::Constant::create(intInputsPrecision, ov::Shape({1}), { axis }), batchDims); diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/grid_sample.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/grid_sample.cpp index 7d7c1d82b8d..278c92ed368 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/grid_sample.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/grid_sample.cpp @@ -103,9 +103,8 @@ protected: std::make_shared(gridPrecision, inputDynamicShapes[1])}; params[0]->set_friendly_name("data"); params[1]->set_friendly_name("grid"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); GridSample::Attributes attributes = {alignCorners, interpolateMode, paddingMode}; - auto gridSampleNode = std::make_shared(paramOuts[0], paramOuts[1], attributes); + auto gridSampleNode = std::make_shared(params[0], params[1], attributes); function = makeNgraphFunction(dataPrecision, params, gridSampleNode, "GridSampleCPU"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/grn.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/grn.cpp index 583bd4535b7..5047d3a615f 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/grn.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/grn.cpp @@ -68,11 +68,10 @@ protected: init_input_shapes({inputShape}); ov::ParameterVector paramsIn; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) paramsIn.push_back(std::make_shared(netPrecision, shape)); - } - const auto paramsOut = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(paramsIn)); - const auto grn = std::make_shared(paramsOut[0], bias); + + const auto grn = std::make_shared(paramsIn[0], bias); const ngraph::ResultVector results{std::make_shared(grn)}; function = std::make_shared(results, paramsIn, "Grn"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/group_convolution.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/group_convolution.cpp index 3d7bd15fd05..7ea599b7c32 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/group_convolution.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/group_convolution.cpp @@ -193,13 +193,11 @@ protected: std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, numGroups, padType) = groupConvParams; ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netType, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); + auto groupConv = std::dynamic_pointer_cast( - ngraph::builder::makeGroupConvolution(paramOuts[0], netType, kernel, stride, padBegin, + ngraph::builder::makeGroupConvolution(params[0], netType, kernel, stride, padBegin, padEnd, dilation, padType, convOutChannels, numGroups)); function = makeNgraphFunction(netType, params, groupConv, "groupConvolution"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/log_softmax.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/log_softmax.cpp index c0c23db047c..4ba51e71dec 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/log_softmax.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/log_softmax.cpp @@ -65,8 +65,7 @@ protected: init_input_shapes(inputShapes); ov::ParameterVector params{std::make_shared(ngPrc, inputDynamicShapes.front())}; - const auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - const auto logSoftmax = std::make_shared(paramOuts[0], axis); + const auto logSoftmax = std::make_shared(params[0], axis); const ngraph::ResultVector results{std::make_shared(logSoftmax)}; function = std::make_shared(results, params, "logSoftmax"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul.cpp index c5508e28f05..ab38ccb1951 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul.cpp @@ -164,8 +164,7 @@ protected: if (secondaryInputType == helpers::InputLayerType::PARAMETER) { params.push_back(std::dynamic_pointer_cast(matrixB)); } - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); - auto matMul = builder::makeMatMul(paramOuts[0], matrixB, transpA, transpB); + auto matMul = builder::makeMatMul(params[0], matrixB, transpA, transpB); function = makeNgraphFunction(netType, params, matMul, cpuNodeType); checkFusingPosition = false; } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul_sparse.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul_sparse.cpp index cf62975e3fd..70f4d833d66 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul_sparse.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/matmul_sparse.cpp @@ -190,12 +190,11 @@ protected: selectedType = makeSelectedTypeStr(selectedType, element::i8); ov::ParameterVector params{std::make_shared(inType, inShapeA)}; - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); auto matrixB = builder::makeDynamicInputLayer(element::f32, helpers::InputLayerType::CONSTANT, inShapeB); auto weiData = generateSparseVector(ngraph::shape_size(inShapeB.get_shape()), weiSparseRate); - auto matMul = makeMatMulRelaxed(paramOuts[0], inShapeB, weiType, transpA, transpB, weiData); + auto matMul = makeMatMulRelaxed(params[0], inShapeB, weiType, transpA, transpB, weiData); function = makeNgraphFunction(element::f32, params, matMul, cpuNodeType); diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/one_hot.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/one_hot.cpp index 84f8c4b4740..6ebc9368e14 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/one_hot.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/one_hot.cpp @@ -137,10 +137,9 @@ protected: params.push_back(depthParam); depth = depthParam; } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto on_value_const = std::make_shared(outType, ngraph::Shape{ }, OnValue); auto off_value_const = std::make_shared(outType, ngraph::Shape{ }, OffValue); - auto oneHot = std::make_shared(paramOuts[0], depth, on_value_const, off_value_const, Axis); + auto oneHot = std::make_shared(params[0], depth, on_value_const, off_value_const, Axis); return makeNgraphFunction(ngraph::element::i32, params, oneHot, "OneHot"); } void generateDepth() { diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/proposal.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/proposal.cpp index 7bb8cae1415..03240dcfdeb 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/proposal.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/proposal.cpp @@ -143,7 +143,6 @@ protected: for (auto&& shape : {inputDynamicShapes[0], inputDynamicShapes[1], inputDynamicShapes[2]}) { params.push_back(std::make_shared(ngPrc, shape)); } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); ngraph::op::ProposalAttrs attrs; attrs.base_size = base_size; @@ -162,7 +161,7 @@ protected: attrs.framework = framework; attrs.infer_probs = true; - auto proposal = std::make_shared(paramOuts[0], paramOuts[1], paramOuts[2], attrs); + auto proposal = std::make_shared(params[0], params[1], params[2], attrs); ngraph::ResultVector results{ std::make_shared(proposal->output(0)), diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/roi_pooling.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/roi_pooling.cpp index c5d3047452a..3b07b93e45e 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/roi_pooling.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/roi_pooling.cpp @@ -203,13 +203,10 @@ protected: auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(ngPrc, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); - auto roi_pooling = ngraph::builder::makeROIPooling(paramOuts[0], paramOuts[1], poolShape, spatial_scale, pool_method); + auto roi_pooling = ngraph::builder::makeROIPooling(params[0], params[1], poolShape, spatial_scale, pool_method); ngraph::ResultVector results{std::make_shared(roi_pooling)}; function = makeNgraphFunction(ngPrc, params, roi_pooling, "ROIPooling"); diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/select.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/select.cpp index 9cacb90f970..84b6a9d19ad 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/select.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/select.cpp @@ -66,8 +66,7 @@ protected: auto param_node = std::make_shared(types[i], inputDynamicShapes[i]); parameters.push_back(param_node); } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(parameters)); - auto select = ngraph::builder::makeSelect(paramOuts, broadcast); + auto select = std::make_shared(parameters[0], parameters[1], parameters[2], broadcast); function = makeNgraphFunction(precision, parameters, select, "Eltwise"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/shapeof.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/shapeof.cpp index 457a2bdfa63..93e5f614894 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/shapeof.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/shapeof.cpp @@ -69,11 +69,10 @@ protected: selectedType = makeSelectedTypeStr("ref", inType); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(inType, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto shapeOf = std::make_shared(paramOuts[0], ngraph::element::i32); + + auto shapeOf = std::make_shared(params[0], ngraph::element::i32); function = makeNgraphFunction(netPrecision, params, shapeOf, "ShapeOf"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/space_to_batch.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/space_to_batch.cpp index bd0493d19af..616474d3a4c 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/space_to_batch.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/space_to_batch.cpp @@ -107,8 +107,7 @@ protected: selectedType = std::string("ref_any_") + netPrecision.name(); ov::ParameterVector params{std::make_shared(ngPrec, inputDynamicShapes.front())}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - paramShape = {paramOuts[0].get_partial_shape().size()}; + paramShape = {params[0]->get_partial_shape().size()}; std::shared_ptr in2, in3, in4; auto blockShapeParam = std::make_shared(ov::element::i64, paramShape); @@ -121,7 +120,7 @@ protected: in4 = padsEndParam; params.push_back(padsEndParam); - auto s2b = std::make_shared(paramOuts[0], in2, in3, in4); + auto s2b = std::make_shared(params[0], in2, in3, in4); function = makeNgraphFunction(inType, params, s2b, "SpaceToBatchCPU"); } }; diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/split.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/split.cpp index ff423786fd4..ae27af687e7 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/split.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/split.cpp @@ -71,12 +71,10 @@ protected: init_input_shapes({inputShapes}); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netPrecision, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); - auto split = std::dynamic_pointer_cast(ngraph::builder::makeSplit(paramOuts[0], + + auto split = std::dynamic_pointer_cast(ngraph::builder::makeSplit(params[0], netPrecision, numSplits, axis)); ngraph::ResultVector results; diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/tile.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/tile.cpp index 32bb1ebc937..a0a68a6f85a 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/tile.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/tile.cpp @@ -99,13 +99,12 @@ protected: } functionParams.front()->set_friendly_name("data"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(functionParams)); std::shared_ptr tileNode; if (isRepeatsConst) { - tileNode = std::make_shared(paramOuts[0], + tileNode = std::make_shared(functionParams[0], ov::op::v0::Constant::create(ov::element::i64, { repeatsData.size() }, repeatsData)); } else { - tileNode = std::make_shared(paramOuts[0], paramOuts[1]); + tileNode = std::make_shared(functionParams[0], functionParams[1]); } function = makeNgraphFunction(netPrecision, functionParams, tileNode, "CPUTile"); } diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/unique.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/unique.cpp index 277a799ba7b..866cdbb9a3f 100644 --- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/unique.cpp +++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/unique.cpp @@ -99,13 +99,12 @@ protected: params.push_back(std::make_shared(dataPrecision, shape)); } params[0]->set_friendly_name("data"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::shared_ptr uniqueNode; if (flattened) { - uniqueNode = std::make_shared(paramOuts[0], sorted); + uniqueNode = std::make_shared(params[0], sorted); } else { axis = std::get<1>(flatOrAxis); - uniqueNode = std::make_shared(paramOuts[0], + uniqueNode = std::make_shared(params[0], ov::op::v0::Constant::create(ov::element::i64, ov::Shape({1}), {axis}), sorted); } diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/add_convert_to_reorder.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/add_convert_to_reorder.cpp index 8be11f4a277..645b85e9816 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/add_convert_to_reorder.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/add_convert_to_reorder.cpp @@ -28,11 +28,9 @@ public: << "Indices vector size and provided indices shape doesn't fit each other"; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); auto indicesNode = ngraph::opset3::Constant::create(secondConstantType, ngraph::Shape(indicesShape), indices); auto axisNode = ngraph::opset3::Constant::create(ngraph::element::i64, ngraph::Shape({}), {axis}); - auto gather = std::make_shared(paramOuts[0], indicesNode, axisNode); + auto gather = std::make_shared(params[0], indicesNode, axisNode); ngraph::ResultVector results{std::make_shared(gather)}; function = std::make_shared(results, params, "gather"); } diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/align_matmul_input_ranks.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/align_matmul_input_ranks.cpp index c5cca71accb..a29927ec6e5 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/align_matmul_input_ranks.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/align_matmul_input_ranks.cpp @@ -56,9 +56,7 @@ protected: const auto ngPrec = element::f32; ov::ParameterVector inputParams{std::make_shared(ngPrec, ov::Shape(inShapes.first)), std::make_shared(ngPrec, ov::Shape(inShapes.second))}; - - const auto outputNodes = helpers::convert2OutputVector(helpers::castOps2Nodes(inputParams)); - const auto matMul = builder::makeMatMul(outputNodes[0], outputNodes[1], false, false); + const auto matMul = builder::makeMatMul(inputParams[0], inputParams[1], false, false); selectedType = makeSelectedTypeStr(with_cpu_x86_avx512_core() ? "brgemm_avx512" : "jit_gemm", ngPrec); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv.cpp index 763251cf5e5..48aea151242 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv.cpp @@ -62,8 +62,7 @@ protected: for (auto&& shape : inputDynamicShapes) { inputParams.push_back(std::make_shared(ngraph::element::f32, shape)); } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); - conv = builder::makeGroupConvolution(paramOuts.front(), element::f32, kernelSize, strides, padBegin, padEnd, dilation, + conv = builder::makeGroupConvolution(inputParams[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels, numOfGroups); ResultVector results; diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv1d.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv1d.cpp index e498ce93074..79a21d4c8bd 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv1d.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_group_conv1d.cpp @@ -67,15 +67,14 @@ protected: for (auto&& shape : inputDynamicShapes) { inputParams.push_back(std::make_shared(ngraph::element::f32, shape)); } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); switch (convType) { case nodeType::convolution : { - conv = builder::makeConvolution(paramOuts.front(), element::f32, kernelSize, strides, padBegin, padEnd, dilation, + conv = builder::makeConvolution(inputParams[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); break; } case nodeType::groupConvolution : { - conv = builder::makeGroupConvolution(paramOuts.front(), element::f32, kernelSize, strides, padBegin, padEnd, dilation, + conv = builder::makeGroupConvolution(inputParams[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels, numOfGroups); break; } diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_reduce_multi_axis.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_reduce_multi_axis.cpp index 5d6424d15f6..3bb5a06c7d9 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_reduce_multi_axis.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/arm/convert_reduce_multi_axis.cpp @@ -67,13 +67,12 @@ protected: for (auto&& shape : inputDynamicShapes) { params.push_back(std::make_shared(ngraph::element::f32, shape)); } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector shapeAxes; shapeAxes.push_back(axes.size()); auto reductionAxesNode = std::dynamic_pointer_cast( std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape(shapeAxes), axes)); - const auto reduce = ngraph::builder::makeReduce(paramOuts[0], reductionAxesNode, keepDims, reductionType); + const auto reduce = ngraph::builder::makeReduce(params[0], reductionAxesNode, keepDims, reductionType); function = makeNgraphFunction(ElementType::f32, params, reduce, "Reduce"); } private: diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv3d_reshape.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv3d_reshape.cpp index e7b1feb6b41..4945a75af3e 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv3d_reshape.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv3d_reshape.cpp @@ -42,7 +42,6 @@ protected: cpuNodeType = nodeType2PluginType(convType); ov::ParameterVector inputParams{std::make_shared(ov::element::f32, ov::Shape{1, 1024, 64})}; - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(inputParams)); std::shared_ptr conv; const std::vector kernelSize = {1}; @@ -55,11 +54,11 @@ protected: const op::PadType paddingType = op::PadType::EXPLICIT; switch (convType) { case nodeType::convolution : { - conv = builder::makeConvolution(paramOuts[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); + conv = builder::makeConvolution(inputParams[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); break; } case nodeType::groupConvolution : { - conv = builder::makeGroupConvolution(paramOuts[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels, + conv = builder::makeGroupConvolution(inputParams[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels, numOfGroups); break; } diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_concat.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_concat.cpp index ec859166e21..e40894ced80 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_concat.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_concat.cpp @@ -66,35 +66,35 @@ void ConvConcatSubgraphTest::SetUp() { ov::ParameterVector inputParams{std::make_shared(ov::element::f32, ov::Shape(inputShapes)), std::make_shared(ov::element::f32, ov::Shape(inputShapes))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); std::vector> convolutionNodes(2); switch (type) { case nodeType::convolution : { for (size_t conv = 0; conv < convolutionNodes.size(); conv++) { - convolutionNodes[conv] = ngraph::builder::makeConvolution(paramOuts[conv], ngraph::element::f32, kernelSize, strides, padBegin, + convolutionNodes[conv] = ngraph::builder::makeConvolution(inputParams[conv], ngraph::element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); } break; } case nodeType::convolutionBackpropData : { for (size_t conv = 0; conv < convolutionNodes.size(); conv++) { - convolutionNodes[conv] = ngraph::builder::makeConvolutionBackpropData(paramOuts[conv], ngraph::element::f32, kernelSize, strides, padBegin, + convolutionNodes[conv] = ngraph::builder::makeConvolutionBackpropData(inputParams[conv], ngraph::element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); } break; } case nodeType::groupConvolution : { for (size_t conv = 0; conv < convolutionNodes.size(); conv++) { - convolutionNodes[conv] = ngraph::builder::makeGroupConvolution(paramOuts[conv], ngraph::element::f32, kernelSize, strides, padBegin, + convolutionNodes[conv] = ngraph::builder::makeGroupConvolution(inputParams[conv], ngraph::element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels, numOfGroups); } break; } case nodeType::groupConvolutionBackpropData : { for (size_t conv = 0; conv < convolutionNodes.size(); conv++) { - convolutionNodes[conv] = ngraph::builder::makeGroupConvolutionBackpropData(paramOuts[conv], ngraph::element::f32, kernelSize, strides, padBegin, - padEnd, dilation, paddingType, numOutChannels, numOfGroups); + convolutionNodes[conv] = ngraph::builder::makeGroupConvolutionBackpropData(inputParams[conv], ngraph::element::f32, kernelSize, + strides, padBegin, padEnd, dilation, paddingType, + numOutChannels, numOfGroups); } break; } diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_maxpool_activ.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_maxpool_activ.cpp index cca2a8ceb69..b9c2a1151cf 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_maxpool_activ.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_maxpool_activ.cpp @@ -33,7 +33,6 @@ protected: std::tie(postOpMgrPtr, fusedOps) = fusingParams; ov::ParameterVector inputParams{std::make_shared(ov::element::f32, ov::Shape{1, 3, 40, 40})}; - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(inputParams)); std::shared_ptr conv; { @@ -44,7 +43,7 @@ protected: const std::vector dilation = {1, 1}; const size_t numOutChannels = 16; const op::PadType paddingType = op::PadType::EXPLICIT; - conv = builder::makeConvolution(paramOuts[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); + conv = builder::makeConvolution(inputParams[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); } std::shared_ptr pooling; { diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_with_zero_point_fuse.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_with_zero_point_fuse.cpp index d5131f3d524..30b8d15950d 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_with_zero_point_fuse.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/conv_with_zero_point_fuse.cpp @@ -51,8 +51,6 @@ void ConvWithZeroPointFuseSubgraphTest::SetUp() { {-12.8f}, {12.7f}); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); - std::vector> branches(2); { ngraph::Strides strides{1, 1}; diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convert_fq_rnn_to_quantized_rnn.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convert_fq_rnn_to_quantized_rnn.cpp index 030cb879234..438cffa8b2b 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convert_fq_rnn_to_quantized_rnn.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convert_fq_rnn_to_quantized_rnn.cpp @@ -113,11 +113,8 @@ protected: std::shared_ptr H; ov::ParameterVector inputParams; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) inputParams.push_back(std::make_shared(ngPrec, shape)); - } - - const auto outputNodes = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); auto makeDataFQ = [](const ngraph::Output& input) { const auto fqLevels = 256; @@ -126,10 +123,10 @@ protected: {-128.f/127}, {1.f}); }; - auto X_FQ = makeDataFQ(outputNodes[0]); + auto X_FQ = makeDataFQ(inputParams[0]); if (quantizedHiddenState) { - H = makeDataFQ(outputNodes[1]); + H = makeDataFQ(inputParams[1]); } else { H = ngraph::builder::makeConstant(ngraph::element::f32, inputDynamicShapes[1].get_shape(), {}, true, 1.f, -1.f); } @@ -159,7 +156,7 @@ protected: if (rnnType == "LSTMSequence") { hasCell = true; - auto C = outputNodes[cellIdx]; + auto C = inputParams[cellIdx]; rnnCellOp = std::make_shared( X_FQ, H, C, seq_lengths, W_FQ, R_FQ, B, hiddenSize, op::RecurrentSequenceDirection::FORWARD); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convs_and_sums.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convs_and_sums.cpp index fa84673b89d..7b4df345dc1 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convs_and_sums.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/convs_and_sums.cpp @@ -38,16 +38,15 @@ protected: auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape{1, 512, 32}), std::make_shared(ngPrc, ov::Shape{1, 128, 32})}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto FQ = ngraph::builder::makeFakeQuantize(paramOuts[1], ngPrc, 256, {}, {-2.8215785026550293}, {2.799535036087036}, + auto FQ = ngraph::builder::makeFakeQuantize(params[1], ngPrc, 256, {}, {-2.8215785026550293}, {2.799535036087036}, {-2.8215785026550293}, {2.799535036087036}); - auto FQ_0 = ngraph::builder::makeFakeQuantize(paramOuts[1], ngPrc, 256, {}, {-5.031249523162842}, {4.991942882537842}, + auto FQ_0 = ngraph::builder::makeFakeQuantize(params[1], ngPrc, 256, {}, {-5.031249523162842}, {4.991942882537842}, {-5.031249523162842}, {4.991942882537842}); auto Add_0 = ngraph::builder::makeEltwise(FQ_0, FQ, EltwiseTypes::ADD); - auto FQ_1 = ngraph::builder::makeFakeQuantize(paramOuts[0], ngPrc, 256, {}, {-2.122633457183838}, {2.106050491333008}, + auto FQ_1 = ngraph::builder::makeFakeQuantize(params[0], ngPrc, 256, {}, {-2.122633457183838}, {2.106050491333008}, {-2.122633457183838}, {2.106050491333008}); auto Const = ngraph::builder::makeConstant(ngPrc, {128, 512, 1}, std::vector{-0.0512377955019474}, false); @@ -58,7 +57,7 @@ protected: auto Add = ngraph::builder::makeEltwise(Add_0, Conv, EltwiseTypes::ADD); - auto FQ_11 = ngraph::builder::makeFakeQuantize(paramOuts[0], ngPrc, 256, {}, {-3.2050728797912598}, {3.1800332069396973}, + auto FQ_11 = ngraph::builder::makeFakeQuantize(params[0], ngPrc, 256, {}, {-3.2050728797912598}, {3.1800332069396973}, {-3.2050728797912598}, {3.1800332069396973}); auto Const_ = ngraph::builder::makeConstant(ngPrc, {128, 512, 1}, std::vector{-0.001183388871140778}, false); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fq_fused_with_ss.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fq_fused_with_ss.cpp index 0e92f4b4d6e..3af1ab6d795 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fq_fused_with_ss.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fq_fused_with_ss.cpp @@ -47,9 +47,8 @@ protected: auto constShift = ngraph::opset5::Constant::create(ngraph::element::f32, sumShape, sumConstData); auto mmConst = ngraph::opset5::Constant::create(ngraph::element::f32, mmShape2, mmInData); ov::ParameterVector mmParams {std::make_shared(ngPrec, mmShape)}; - const auto mmOutputNodes = helpers::convert2OutputVector(helpers::castOps2Nodes(mmParams)); - const auto mm = builder::makeMatMul(mmOutputNodes[0], mmConst, false, false); + const auto mm = builder::makeMatMul(mmParams[0], mmConst, false, false); auto sum = ngraph::builder::makeEltwise(constShift, mm, ngraph::helpers::EltwiseTypes::ADD); auto fq = ngraph::builder::makeFakeQuantize(sum, ngraph::element::f32, 256, {}, {-8.0f}, {7.0f}, {-8.0f}, {7.0f}); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fullyconnected_strided_inputs_outputs.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fullyconnected_strided_inputs_outputs.cpp index 070ab78d782..be89ca0cafa 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fullyconnected_strided_inputs_outputs.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/fullyconnected_strided_inputs_outputs.cpp @@ -48,9 +48,8 @@ protected: ov::ParameterVector params {std::make_shared(ngPrec, ov::Shape(splitShape))}; - const auto splitOutputNodes = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); const auto splitAxis = rank == 3 ? 1 : 0; - const auto split = builder::makeSplit(splitOutputNodes[0], ngPrec, 2 /* splits */, splitAxis); + const auto split = builder::makeSplit(params[0], ngPrec, 2 /* splits */, splitAxis); SizeVector fcWeightsShape{16, 8}; if (rank == 3) bcastTo3D(fcWeightsShape); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_decompress_convert.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_decompress_convert.cpp index 06e4624ad77..e041cbb2887 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_decompress_convert.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_decompress_convert.cpp @@ -209,7 +209,6 @@ protected: selectedType = makeSelectedTypeStr(selectedType, outType); ov::ParameterVector params{std::make_shared(inType, inShapeA)}; - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); std::shared_ptr inputB = builder::makeConstant(weiConstElemType, inShapeB.get_shape(), {}, true); if (weiConstElemType == ElementType::f16) { inputB = std::make_shared(inputB, convertOutType); @@ -217,7 +216,7 @@ protected: } expectedWeiConstElemType = weiConstElemType; - auto matMul = builder::makeMatMul(paramOuts[0], inputB, transpA, transpB); + auto matMul = builder::makeMatMul(params[0], inputB, transpA, transpB); function = CPUTestsBase::makeNgraphFunction(netType, params, matMul, cpuNodeType); } @@ -494,7 +493,6 @@ protected: for (auto&& shape : {inShapeFC0, inShapeFC1}) { params.push_back(std::make_shared(inType, shape)); } - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); std::shared_ptr inputWeights = builder::makeConstant(weiConstElemType, inShapeWeights.get_shape(), {}, true); if (weiConstElemType == ElementType::f16) { inputWeights = std::make_shared(inputWeights, convertOutType); @@ -503,8 +501,8 @@ protected: // In this test, convert must be folded on the ngraph side, so the constant with fp32 precision is expected expectedWeiConstElemType = ElementType::f32; - auto matMul0 = builder::makeMatMul(paramOuts[0], inputWeights, transpA, transpB); - auto matMul1 = builder::makeMatMul(paramOuts[1], inputWeights, transpA, transpB); + auto matMul0 = builder::makeMatMul(params[0], inputWeights, transpA, transpB); + auto matMul1 = builder::makeMatMul(params[1], inputWeights, transpA, transpB); auto concat = builder::makeConcat({matMul0, matMul1}, 0); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_strided_inputs_outputs.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_strided_inputs_outputs.cpp index c5c1a43fbd8..5a20c437d36 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_strided_inputs_outputs.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/matmul_strided_inputs_outputs.cpp @@ -36,8 +36,7 @@ protected: SizeVector splitShape{1, 2, 1, 16}; ov::ParameterVector splitInputParams {std::make_shared(ngPrec, ov::Shape(splitShape))}; - const auto splitOutputNodes = helpers::convert2OutputVector(helpers::castOps2Nodes(splitInputParams)); - const auto split = builder::makeSplit(splitOutputNodes[0], ngPrec, 2 /* splits */, 1 /* 2nd axis */); + const auto split = builder::makeSplit(splitInputParams[0], ngPrec, 2 /* splits */, 1 /* 2nd axis */); std::vector concatShapes{{1, 1, 8, 8}, {1, 1, 8, 8}}; ov::ParameterVector concatInputParams {std::make_shared(ngPrec, concatShapes[0]), @@ -49,9 +48,8 @@ protected: SizeVector matmulShape{1, 1, 16, 8}; ov::ParameterVector matmulInputParams {std::make_shared(ngPrec, ov::Shape(matmulShape))}; - const auto matmulOutputNodes = helpers::convert2OutputVector(helpers::castOps2Nodes(matmulInputParams)); - const auto matMul2 = builder::makeMatMul(split->output(1), matmulOutputNodes[0], false, false); + const auto matMul2 = builder::makeMatMul(split->output(1), matmulInputParams[0], false, false); const auto concatMatMuls = builder::makeConcat({matMul1, matMul2}, 2 /* 3rd axis */); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/not_fused_conv_simple_op.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/not_fused_conv_simple_op.cpp index 8cc7569233a..4229e152826 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/not_fused_conv_simple_op.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/not_fused_conv_simple_op.cpp @@ -17,7 +17,6 @@ protected: ov::ParameterVector inputParams{std::make_shared(ov::element::f32, ov::Shape{1, 3, 12, 9}), std::make_shared(ov::element::f32, ov::Shape{1, 16, 12, 9})}; - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(inputParams)); std::shared_ptr conv; { @@ -28,12 +27,12 @@ protected: const std::vector dilation = {1, 1}; const size_t numOutChannels = 16; const op::PadType paddingType = op::PadType::EXPLICIT; - conv = builder::makeConvolution(paramOuts[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); + conv = builder::makeConvolution(inputParams[0], element::f32, kernelSize, strides, padBegin, padEnd, dilation, paddingType, numOutChannels); } const auto sharedNode = builder::makeConstant(element::f32, {1, 16, 1, 1}, std::vector{}, true); const auto postOpCandidate = builder::makeEltwise(conv, sharedNode, EltwiseTypes::ADD); - const auto secondConsumpt = builder::makeEltwise(paramOuts[1], sharedNode, EltwiseTypes::ADD); + const auto secondConsumpt = builder::makeEltwise(inputParams[1], sharedNode, EltwiseTypes::ADD); NodeVector results{postOpCandidate, secondConsumpt}; function = std::make_shared(results, inputParams, "NotFusedConvSimpleOp"); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/split_matmul_concat.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/split_matmul_concat.cpp index 2a57e1cc413..aeaa041df6c 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/split_matmul_concat.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/split_matmul_concat.cpp @@ -107,10 +107,9 @@ protected: const auto& inShapeB = inputDynamicShapes[1]; ov::ParameterVector params{std::make_shared(ElementType::f32, inShapeA)}; - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); std::shared_ptr inputB = builder::makeConstant(ElementType::f32, inShapeB.get_shape(), {}, true); - auto split = builder::makeVariadicSplit(paramOuts[0], {1, 1}, 0); + auto split = builder::makeVariadicSplit(params[0], {1, 1}, 0); auto matMul = builder::makeMatMul(split->output(0), inputB, transpA, transpB); diff --git a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/tile_with_two_output_edges.cpp b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/tile_with_two_output_edges.cpp index 8fdfbff0827..00a8b168a21 100644 --- a/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/tile_with_two_output_edges.cpp +++ b/src/plugins/intel_cpu/tests/functional/subgraph_tests/src/tile_with_two_output_edges.cpp @@ -17,9 +17,8 @@ protected: auto ngPrc = element::f32; ov::ParameterVector inputParams {std::make_shared(ngPrc, ov::Shape{1, 3, 12, 9})}; - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(inputParams)); - auto tile = ngraph::builder::makeTile(paramOuts[0], std::vector{1, 2, 1, 1}); + auto tile = ngraph::builder::makeTile(inputParams[0], std::vector{1, 2, 1, 1}); const auto const1 = ngraph::builder::makeConstant(ngPrc, std::vector{1, 6, 1, 1}, std::vector{}, true); const auto const2 = ngraph::builder::makeConstant(ngPrc, std::vector{1, 6, 1, 1}, std::vector{}, true); diff --git a/src/plugins/intel_cpu/tests/functional/test_utils/fusing_test_utils.hpp b/src/plugins/intel_cpu/tests/functional/test_utils/fusing_test_utils.hpp index 32d22393bef..d802e3b550f 100644 --- a/src/plugins/intel_cpu/tests/functional/test_utils/fusing_test_utils.hpp +++ b/src/plugins/intel_cpu/tests/functional/test_utils/fusing_test_utils.hpp @@ -362,9 +362,7 @@ const auto fusingSum = fusingSpecificParams{std::make_shared(std:: auto shape = cfg.input->get_output_partial_shape(0); ov::ParameterVector newParams{std::make_shared(cfg.type, shape)}; cfg.params.insert(cfg.params.end(), newParams.begin(), newParams.end()); - auto newParamOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(newParams)); - return std::make_shared(cfg.input, newParamOuts[0]); + return std::make_shared(cfg.input, newParams[0]); }, "Add(Parameters)"}}), {"Add"}}; const auto fusingSumEluFQ = fusingSpecificParams{std::make_shared(std::vector{ @@ -372,9 +370,7 @@ const auto fusingSumEluFQ = fusingSpecificParams{std::make_shared( auto shape = cfg.input->get_output_partial_shape(0); ov::ParameterVector newParams{std::make_shared(cfg.type, shape)}; cfg.params.insert(cfg.params.end(), newParams.begin(), newParams.end()); - auto newParamOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(newParams)); - return std::make_shared(cfg.input, newParamOuts[0]); + return std::make_shared(cfg.input, newParams[0]); }, "Add(Parameters)"}, {[](postNodeConfig& cfg){ return ngraph::builder::makeActivation(cfg.input, cfg.type, ngraph::helpers::Elu, {}, {2.0f}); diff --git a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp index e6b35e83565..e3c570c393a 100644 --- a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp +++ b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp @@ -103,14 +103,13 @@ void ConvolutionLayerTestFixture::SetUp() { std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType) = convParams; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector filter_weights; auto filter_size = std::accumulate(std::begin(kernel), std::end(kernel), 1, std::multiplies()); filter_weights = ov::test::utils::generate_float_numbers(convOutChannels * inputShape[1] * filter_size, -0.1f, 0.1f); - auto conv = std::dynamic_pointer_cast(ngraph::builder::makeConvolution(paramOuts[0], + auto conv = std::dynamic_pointer_cast(ngraph::builder::makeConvolution(params[0], ngPrc, kernel, stride, diff --git a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp index af9dab4bdd8..2efdb5d1ef3 100644 --- a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp +++ b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp @@ -58,7 +58,6 @@ protected: ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShapes[0])), std::make_shared(ngPrc, ov::Shape(inputShapes[1]))}; std::vector WRB = {inputShapes[2], inputShapes[3], inputShapes[4]}; - auto in = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector weights_vals = ov::test::utils::generate_float_numbers(ngraph::shape_size(WRB[0]), -0.0001f, 0.0001f); std::vector reccurrenceWeights_vals = @@ -70,8 +69,8 @@ protected: auto reccurrenceWeightsNode = ngraph::builder::makeConstant(ngPrc, WRB[1], reccurrenceWeights_vals); auto biasNode = ngraph::builder::makeConstant(ngPrc, WRB[2], bias_vals); - auto gru_cell = std::make_shared(in[0], - in[1], + auto gru_cell = std::make_shared(params[0], + params[1], weightsNode, reccurrenceWeightsNode, biasNode, diff --git a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp index 9dd9e6e4383..598ca516742 100644 --- a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp +++ b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp @@ -62,7 +62,6 @@ protected: std::vector WRB = {inputShapes[3], inputShapes[4], inputShapes[5], inputShapes[2]}; - auto in = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector weights_vals = ov::test::utils::generate_float_numbers(ngraph::shape_size(WRB[0]), -0.0001f, 0.0001f); std::vector reccurrenceWeights_vals = @@ -74,13 +73,13 @@ protected: auto reccurrenceWeightsNode = ngraph::builder::makeConstant(ngPrc, WRB[1], reccurrenceWeights_vals); auto biasNode = ngraph::builder::makeConstant(ngPrc, WRB[2], bias_vals); - std::vector lengths(in[0].get_partial_shape()[0].get_min_length(), - in[0].get_partial_shape()[1].get_min_length()); + std::vector lengths(params[0]->get_partial_shape()[0].get_min_length(), + params[0]->get_partial_shape()[1].get_min_length()); std::shared_ptr seq_length = ngraph::builder::makeConstant(ngraph::element::i64, WRB[3], lengths, false); - auto gru_sequence = std::make_shared(in[0], - in[1], + auto gru_sequence = std::make_shared(params[0], + params[1], seq_length, weightsNode, reccurrenceWeightsNode, diff --git a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp index 7e519c3f7d1..0b7ea4daa08 100644 --- a/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp +++ b/src/plugins/intel_gna/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp @@ -61,7 +61,6 @@ protected: std::make_shared(ngPrc, ov::Shape(inputShapes[2]))}; std::vector WRB = {inputShapes[4], inputShapes[5], inputShapes[6], inputShapes[3]}; - auto in = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector weights_vals = ov::test::utils::generate_float_numbers(ngraph::shape_size(WRB[0]), -0.0001f, 0.0001f); @@ -74,13 +73,13 @@ protected: auto reccurrenceWeightsNode = ngraph::builder::makeConstant(ngPrc, WRB[1], reccurrenceWeights_vals); auto biasNode = ngraph::builder::makeConstant(ngPrc, WRB[2], bias_vals); - std::vector lengths(in[0].get_partial_shape()[0].get_min_length(), - in[0].get_partial_shape()[1].get_min_length()); + std::vector lengths(params[0]->get_partial_shape()[0].get_min_length(), + params[0]->get_partial_shape()[1].get_min_length()); std::shared_ptr seq_length = ngraph::builder::makeConstant(ngraph::element::i64, WRB[3], lengths, false); - auto lstm_sequence = std::make_shared(in[0], - in[1], - in[2], + auto lstm_sequence = std::make_shared(params[0], + params[1], + params[2], seq_length, weightsNode, reccurrenceWeightsNode, diff --git a/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/topk.cpp b/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/topk.cpp index 100c33bb788..248f0b72a0f 100644 --- a/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/topk.cpp +++ b/src/plugins/intel_gpu/tests/functional/shared_tests_instances/single_layer_tests/topk.cpp @@ -74,11 +74,10 @@ void TopKLayerTestGPU::SetUp() { auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramIn = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto k = std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape{}, &keepK); auto topk = std::dynamic_pointer_cast( - std::make_shared(paramIn[0], k, axis, mode, sort, ngraph::element::Type_t::i64, stable)); + std::make_shared(params[0], k, axis, mode, sort, ngraph::element::Type_t::i64, stable)); ngraph::ResultVector results; for (size_t i = 0; i < topk->get_output_size(); i++) { diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/convolution.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/convolution.cpp index de10fba3cfc..ca0c19bd3f3 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/convolution.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/convolution.cpp @@ -85,12 +85,10 @@ protected: std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType) = convParams; ov::ParameterVector inputParams; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) inputParams.push_back(std::make_shared(inType, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); - auto convolutionNode = ngraph::builder::makeConvolution(paramOuts.front(), netType, kernel, stride, padBegin, + auto convolutionNode = ngraph::builder::makeConvolution(inputParams.front(), netType, kernel, stride, padBegin, padEnd, dilation, padType, convOutChannels); ngraph::ResultVector results; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/broadcast.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/broadcast.cpp index 580a67383f3..8b7c750756b 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/broadcast.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/broadcast.cpp @@ -109,8 +109,6 @@ protected: } functionParams.front()->set_friendly_name("data"); - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(functionParams)); - std::shared_ptr broadcastOp; if (mode == ov::op::BroadcastType::EXPLICIT) { std::shared_ptr targetShapeOp; @@ -125,19 +123,19 @@ protected: } else { axesMappingOp = functionParams.size() > 2 ? functionParams[2] : functionParams[1]; } - broadcastOp = std::make_shared(paramOuts[0], + broadcastOp = std::make_shared(functionParams[0], targetShapeOp, axesMappingOp, mode); } else if (mode == ov::op::BroadcastType::NUMPY) { if (isTargetShapeConst) { auto targetShapeConst = ov::op::v0::Constant::create(ov::element::i64, {targetShapeRank}, targetShape); - broadcastOp = std::make_shared(paramOuts[0], + broadcastOp = std::make_shared(functionParams[0], targetShapeConst, mode); } else { - broadcastOp = std::make_shared(paramOuts[0], - paramOuts[1], + broadcastOp = std::make_shared(functionParams[0], + functionParams[1], mode); } } diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/convolution.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/convolution.cpp index a3c84e5cd51..cf9ae70ee7f 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/convolution.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/convolution.cpp @@ -96,12 +96,10 @@ protected: } ov::ParameterVector inputParams; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) inputParams.push_back(std::make_shared(inType, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); - auto convolutionNode = ngraph::builder::makeConvolution(paramOuts.front(), netType, kernel, stride, padBegin, + auto convolutionNode = ngraph::builder::makeConvolution(inputParams.front(), netType, kernel, stride, padBegin, padEnd, dilation, padType, convOutChannels); if (activationFusing) { auto activationNode = ngraph::builder::makeActivation(convolutionNode, netType, ngraph::helpers::ActivationTypes::Relu); diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/detection_output.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/detection_output.cpp index a5dfc13c5c8..e58f749c93e 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/detection_output.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/detection_output.cpp @@ -196,24 +196,23 @@ protected: init_input_shapes({ inShapes }); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(ngraph::element::f32, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); if (attrs.num_classes == -1) { std::shared_ptr detOut; - if (paramOuts.size() == 3) - detOut = std::make_shared(paramOuts[0], paramOuts[1], paramOuts[2], attrs); - else if (paramOuts.size() == 5) - detOut = std::make_shared(paramOuts[0], paramOuts[1], paramOuts[2], paramOuts[3], paramOuts[4], attrs); + if (params.size() == 3) + detOut = std::make_shared(params[0], params[1], params[2], attrs); + else if (params.size() == 5) + detOut = std::make_shared(params[0], params[1], params[2], params[3], params[4], attrs); else throw std::runtime_error("DetectionOutput layer supports only 3 or 5 inputs"); ngraph::ResultVector results{std::make_shared(detOut)}; function = std::make_shared(results, params, "DetectionOutputDynamic"); } else { + auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto detOut = ngraph::builder::makeDetectionOutput(paramOuts, attrs); ngraph::ResultVector results{std::make_shared(detOut)}; function = std::make_shared(results, params, "DetectionOutputDynamic"); diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather.cpp index b97dd992700..bdda5ccbe2a 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather.cpp @@ -119,14 +119,11 @@ protected: params.back()->set_friendly_name("axis"); } - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - - gatherNode = std::make_shared(paramOuts[0], - isIndicesConstant ? indicesNode : paramOuts[1], + gatherNode = std::make_shared(params[0], + isIndicesConstant ? indicesNode : params[1], isAxisConstant ? axisNode - : isIndicesConstant ? paramOuts[1] - : paramOuts[2], + : isIndicesConstant ? params[1] + : params[2], batchDims); ngraph::ResultVector results{std::make_shared(gatherNode)}; function = std::make_shared(results, params, "Gather"); diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather_nd.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather_nd.cpp index cdd9ace9922..f3d98ff82de 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather_nd.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/gather_nd.cpp @@ -100,11 +100,8 @@ protected: params.back()->set_friendly_name("indices"); } - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - - gather_ndNode = std::make_shared(paramOuts[0], - isIndicesConstant ? indicesNode : paramOuts[1], + gather_ndNode = std::make_shared(params[0], + isIndicesConstant ? indicesNode : params[1], batchDims); ngraph::ResultVector results{std::make_shared(gather_ndNode)}; function = std::make_shared(results, params, "GatherND"); diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/grid_sample.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/grid_sample.cpp index fb9c60318be..11862e3d42c 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/grid_sample.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/grid_sample.cpp @@ -83,9 +83,8 @@ protected: std::make_shared(gridPrecision, inputDynamicShapes[1])}; params[0]->set_friendly_name("data"); params[1]->set_friendly_name("grid"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); GridSample::Attributes attributes = {alignCorners, interpolateMode, paddingMode}; - auto gridSampleNode = std::make_shared(paramOuts[0], paramOuts[1], attributes); + auto gridSampleNode = std::make_shared(params[0], params[1], attributes); ngraph::ResultVector results; for (size_t i = 0; i < gridSampleNode->get_output_size(); i++) { diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/groupconvolution.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/groupconvolution.cpp index e47866f1f57..01fad8fc9f6 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/groupconvolution.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/groupconvolution.cpp @@ -87,12 +87,10 @@ protected: std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, numGroups, padType) = groupConvParams; ov::ParameterVector inputParams; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) inputParams.push_back(std::make_shared(inType, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(inputParams)); - auto groupConvolutionNode = ngraph::builder::makeGroupConvolution(paramOuts.front(), netType, kernel, stride, padBegin, + auto groupConvolutionNode = ngraph::builder::makeGroupConvolution(inputParams.front(), netType, kernel, stride, padBegin, padEnd, dilation, padType, convOutChannels, numGroups); ngraph::ResultVector results; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/matmul.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/matmul.cpp index 8965a42ee35..45348753685 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/matmul.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/matmul.cpp @@ -122,8 +122,7 @@ protected: if (secondaryInputType == helpers::InputLayerType::PARAMETER) { params.push_back(std::dynamic_pointer_cast(matrixB)); } - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(params)); - auto matMul = builder::makeMatMul(paramOuts[0], matrixB, transpA, transpB); + auto matMul = builder::makeMatMul(params[0], matrixB, transpA, transpB); auto makeFunction = [](const ngraph::element::Type &ngPrc, ngraph::ParameterVector ¶ms, const std::shared_ptr &lastNode) { ngraph::ResultVector results; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/mvn.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/mvn.cpp index 2dee03efde1..4d58cb59f84 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/mvn.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/mvn.cpp @@ -72,12 +72,11 @@ protected: std::string eps_mode = "inside_sqrt"; ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netPrecision, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); + auto axesNode = ngraph::builder::makeConstant(axesType, ngraph::Shape{axes.size()}, axes); - auto mvn = ngraph::builder::makeMVN6(paramOuts[0], axesNode, normalizeVariance, eps, eps_mode); + auto mvn = ngraph::builder::makeMVN6(params[0], axesNode, normalizeVariance, eps, eps_mode); rel_threshold = 0.015f; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/normalize_l2.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/normalize_l2.cpp index 7d4adb660fe..f955ef243a2 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/normalize_l2.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/normalize_l2.cpp @@ -56,11 +56,10 @@ protected: init_input_shapes({inputShapes}); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netPrecision, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto normalize = ngraph::builder::makeNormalizeL2(paramOuts[0], axes, eps, epsMode); + + auto normalize = ngraph::builder::makeNormalizeL2(params[0], axes, eps, epsMode); ngraph::ResultVector results{std::make_shared(normalize)}; function = std::make_shared(results, params, "NormalizeL2"); diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/pad.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/pad.cpp index d219b693016..4a30f042df0 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/pad.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/pad.cpp @@ -121,8 +121,7 @@ protected: arg_pad_value = std::make_shared(inType, ngraph::Shape{}, &argPadValue); } - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(functionParams)); - auto pad = std::make_shared(paramOuts[0], pads_begin, pads_end, arg_pad_value, padMode); + auto pad = std::make_shared(functionParams[0], pads_begin, pads_end, arg_pad_value, padMode); ngraph::ResultVector results; for (size_t i = 0; i < pad->get_output_size(); ++i) { diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/prior_box.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/prior_box.cpp index 9c22ee657ee..6c3ad3f168f 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/prior_box.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/prior_box.cpp @@ -95,13 +95,11 @@ protected: auto strideInput = ngraph::opset1::Constant::create(ngraph::element::i32, ngraph::Shape{1}, {1}); ov::ParameterVector functionParams; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) functionParams.push_back(std::make_shared(inType, shape)); - } - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(functionParams)); - auto shapeOfOp1 = std::make_shared(paramOuts[0], element::i32); - auto shapeOfOp2 = std::make_shared(paramOuts[1], element::i32); + auto shapeOfOp1 = std::make_shared(functionParams[0], element::i32); + auto shapeOfOp2 = std::make_shared(functionParams[1], element::i32); auto stridedSliceOp1 = ngraph::builder::makeStridedSlice(shapeOfOp1, beginInput, endInput, strideInput, element::i32, diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/reduce.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/reduce.cpp index 1f13d7998a6..e4ae7b23381 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/reduce.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/reduce.cpp @@ -78,11 +78,8 @@ protected: init_input_shapes(inputShapes); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netPrecision, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); std::vector shapeAxes; shapeAxes.push_back(axes.size()); @@ -90,7 +87,7 @@ protected: auto reductionAxesNode = std::dynamic_pointer_cast( std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape(shapeAxes), axes)); - const auto reduce = ngraph::builder::makeReduce(paramOuts[0], reductionAxesNode, keepDims, reductionType); + const auto reduce = ngraph::builder::makeReduce(params[0], reductionAxesNode, keepDims, reductionType); auto makeFunction = [](ParameterVector ¶ms, const std::shared_ptr &lastNode) { ResultVector results; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/roi_pooling.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/roi_pooling.cpp index 34ac60f2752..5add9f1cc1d 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/roi_pooling.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/roi_pooling.cpp @@ -183,13 +183,10 @@ protected: auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(ngPrc, shape)); - } - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); - auto roi_pooling = ngraph::builder::makeROIPooling(paramOuts[0], paramOuts[1], poolShape, spatial_scale, pool_method); + auto roi_pooling = ngraph::builder::makeROIPooling(params[0], params[1], poolShape, spatial_scale, pool_method); ngraph::ResultVector results; for (size_t i = 0; i < roi_pooling->get_output_size(); i++) diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp index c1217d68744..d231567a6a3 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp @@ -54,11 +54,10 @@ protected: outType = ElementType::i32; ov::ParameterVector functionParams; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) functionParams.push_back(std::make_shared(netPrecision, shape)); - } - auto paramOuts = helpers::convert2OutputVector(helpers::castOps2Nodes(functionParams)); - auto shapeOfOp = std::make_shared(paramOuts[0], element::i32); + + auto shapeOfOp = std::make_shared(functionParams[0], element::i32); auto makeFunction = [](ParameterVector ¶ms, const std::shared_ptr &lastNode) { ResultVector results; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/softmax.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/softmax.cpp index a8cc19ea0cb..5de070d5fab 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/softmax.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/softmax.cpp @@ -53,14 +53,10 @@ protected: init_input_shapes({inShape}); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(inType, shape)); - } - const auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - - const auto softMax = std::make_shared(paramOuts.at(0), axis); + const auto softMax = std::make_shared(params.at(0), axis); auto makeFunction = [](ParameterVector ¶ms, const std::shared_ptr &lastNode) { ResultVector results; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp index 472960b7574..d922da0efc3 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp @@ -66,10 +66,8 @@ protected: } init_input_shapes({inputShape}); ov::ParameterVector dyn_params{std::make_shared(netPrecision, inputDynamicShapes[0])}; - auto paramOuts = - ngraph::helpers::convert2OutputVector(helpers::castOps2Nodes(dyn_params)); auto split = std::dynamic_pointer_cast( - ngraph::builder::makeSplit(paramOuts[0], netPrecision, numSplits, axis)); + ngraph::builder::makeSplit(dyn_params[0], netPrecision, numSplits, axis)); ngraph::ResultVector results; for (size_t i = 0; i < outIndices.size(); i++) { results.push_back(std::make_shared(split->output(outIndices[i]))); @@ -205,7 +203,6 @@ protected: init_input_shapes(inputShapes); ov::ParameterVector dyn_params{std::make_shared(netPrecision, inputDynamicShapes[0])}; - auto paramOuts = ngraph::helpers::convert2OutputVector(helpers::castOps2Nodes(dyn_params)); auto splitAxisOp = std::make_shared(ngraph::element::i64, ngraph::Shape{}, std::vector{static_cast(axis)}); @@ -218,7 +215,7 @@ protected: splitLengthOp = std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape{splitLength.size()}, splitLength); } - auto varSplit = std::make_shared(paramOuts[0], splitAxisOp, splitLengthOp); + auto varSplit = std::make_shared(dyn_params[0], splitAxisOp, splitLengthOp); ngraph::ResultVector results; for (size_t i = 0; i < splitLength.size(); i++) { results.push_back(std::make_shared(varSplit->output(i))); diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/tile.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/tile.cpp index 3f3e0734eb2..2c1268d76db 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/tile.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/tile.cpp @@ -93,13 +93,12 @@ protected: } functionParams.front()->set_friendly_name("data"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(functionParams)); std::shared_ptr tileNode; if (isRepeatsConst) { - tileNode = std::make_shared(paramOuts[0], + tileNode = std::make_shared(functionParams[0], ov::op::v0::Constant::create(ov::element::i64, { repeatsData.size() }, repeatsData)); } else { - tileNode = std::make_shared(paramOuts[0], paramOuts[1]); + tileNode = std::make_shared(functionParams[0], functionParams[1]); } ngraph::ResultVector results; diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/unique.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/unique.cpp index a8bf9bc5173..9e60d64fb7d 100644 --- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/unique.cpp +++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/unique.cpp @@ -74,15 +74,13 @@ protected: params.push_back(std::make_shared(dataPrecision, shape)); } params[0]->set_friendly_name("data"); - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::shared_ptr uniqueNode; if (flattened) { - uniqueNode = std::make_shared(paramOuts[0], sorted); + uniqueNode = std::make_shared(params[0], sorted); } else { axis = std::get<1>(flatOrAxis); uniqueNode = std::make_shared( - paramOuts[0], + params[0], ov::op::v0::Constant::create(ov::element::i64, ov::Shape({1}), {axis}), sorted); } diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_model_static_split_layer.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_model_static_split_layer.cpp index 0f38bf1787b..65810269414 100644 --- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_model_static_split_layer.cpp +++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_model_static_split_layer.cpp @@ -79,10 +79,8 @@ protected: const auto inShapSplit = inputDynamicShapes[0]; const auto inShapeElt = inputDynamicShapes[1]; ov::ParameterVector params; - for (auto&& shape : {inShapSplit, inShapeElt}) { + for (auto&& shape : {inShapSplit, inShapeElt}) params.push_back(std::make_shared(netType, shape)); - } - auto paramOuts = helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto axis = ngraph::opset1::Constant::create(ngraph::element::i64, ngraph::Shape{}, {0}); axis->set_friendly_name("axis"); @@ -90,10 +88,10 @@ protected: auto split_sizes = ngraph::opset1::Constant::create(ngraph::element::i64, ngraph::Shape{2}, {1, 1}); split_sizes->set_friendly_name("split_sizes"); - auto variadicSplitOp = std::make_shared(paramOuts[0], axis, split_sizes); + auto variadicSplitOp = std::make_shared(params[0], axis, split_sizes); variadicSplitOp->set_friendly_name("variadicSplit"); - auto addOp = ngraph::builder::makeEltwise(paramOuts[1], variadicSplitOp->output(1), ngraph::helpers::EltwiseTypes::ADD); + auto addOp = ngraph::builder::makeEltwise(params[1], variadicSplitOp->output(1), ngraph::helpers::EltwiseTypes::ADD); addOp->set_friendly_name("add"); ngraph::ResultVector results = {std::make_shared(addOp)}; diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_gen_impl_key.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_gen_impl_key.cpp index 06aa4a11817..c365f1cd888 100644 --- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_gen_impl_key.cpp +++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_gen_impl_key.cpp @@ -84,12 +84,10 @@ protected: const auto inShapeShapeOf = inputDynamicShapes[0]; const auto inShapeElt = inputDynamicShapes[1]; ov::ParameterVector params; - for (auto&& shape : {inShapeShapeOf, inShapeElt}) { + for (auto&& shape : {inShapeShapeOf, inShapeElt}) params.push_back(std::make_shared(netType, shape)); - } - auto paramOuts = helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto addOp1 = ngraph::builder::makeEltwise(paramOuts[1], paramOuts[1], ngraph::helpers::EltwiseTypes::ADD); + auto addOp1 = ngraph::builder::makeEltwise(params[1], params[1], ngraph::helpers::EltwiseTypes::ADD); addOp1->set_friendly_name("add1"); auto shapeOfOp1 = std::make_shared(addOp1, ElementType::i64); @@ -110,7 +108,7 @@ protected: auto reshapeOp1 = std::make_shared(addOp1, concatOp1, false); reshapeOp1->set_friendly_name("reshapeOp1"); - auto addOp2 = ngraph::builder::makeEltwise(paramOuts[1], paramOuts[1], ngraph::helpers::EltwiseTypes::ADD); + auto addOp2 = ngraph::builder::makeEltwise(params[1], params[1], ngraph::helpers::EltwiseTypes::ADD); addOp2->set_friendly_name("add2"); auto shapeOfOp2 = std::make_shared(addOp2, ElementType::i64); diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_reduce_deconvolution_concat.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_reduce_deconvolution_concat.cpp index f09470c91a8..5ddc7977e27 100644 --- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_reduce_deconvolution_concat.cpp +++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_reduce_deconvolution_concat.cpp @@ -81,19 +81,17 @@ protected: init_input_shapes(inputShapes); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netType, shape)); - } - auto paramOuts = helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto deconvOp = ngraph::builder::makeConvolutionBackpropData(paramOuts[0], netType, {2, 2, 2}, {2, 2, 2}, {0, 0, 0}, + auto deconvOp = ngraph::builder::makeConvolutionBackpropData(params[0], netType, {2, 2, 2}, {2, 2, 2}, {0, 0, 0}, {0, 0, 0}, {1, 1, 1}, ov::op::PadType::EXPLICIT, 16); deconvOp->set_friendly_name("deconv"); std::vector reduce_axes = {5}; auto reduceAxesNode = std::dynamic_pointer_cast( std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape({1}), reduce_axes)); - auto reduceOp = ngraph::builder::makeReduce(paramOuts[1], reduceAxesNode, false, ngraph::helpers::ReductionType::Max); + auto reduceOp = ngraph::builder::makeReduce(params[1], reduceAxesNode, false, ngraph::helpers::ReductionType::Max); reduceOp->set_friendly_name("reduce"); auto concatOp = ngraph::builder::makeConcat({deconvOp, reduceOp}, 1); diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_activation.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_activation.cpp index 4967c716b14..815a2954acb 100644 --- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_activation.cpp +++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_activation.cpp @@ -92,15 +92,13 @@ protected: init_input_shapes({inputShape}); ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netType, shape)); - } - auto paramOuts = helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector shape_pattern = {0, 1, -1, 0}; auto shapePatternsNode = std::dynamic_pointer_cast( std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape({4}), shape_pattern)); - auto reshapeOp = std::make_shared(paramOuts[0], shapePatternsNode, true); + auto reshapeOp = std::make_shared(params[0], shapePatternsNode, true); reshapeOp->set_friendly_name("reshape"); auto shapeOfOp = std::make_shared(reshapeOp, ElementType::i32); diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_reduce_reshape.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_reduce_reshape.cpp index 107cb0f2bcd..ce39dfc1225 100644 --- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_reduce_reshape.cpp +++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_shape_of_reduce_reshape.cpp @@ -84,15 +84,13 @@ protected: const auto inShapeShapeOf = inputDynamicShapes[0]; const auto inShapeElt = inputDynamicShapes[1]; ov::ParameterVector params; - for (auto&& shape : inputDynamicShapes) { + for (auto&& shape : inputDynamicShapes) params.push_back(std::make_shared(netType, shape)); - } - auto paramOuts = helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto addOp = ngraph::builder::makeEltwise(paramOuts[1], paramOuts[1], ngraph::helpers::EltwiseTypes::ADD); + auto addOp = ngraph::builder::makeEltwise(params[1], params[1], ngraph::helpers::EltwiseTypes::ADD); addOp->set_friendly_name("add"); - auto shapeOfOp1 = std::make_shared(paramOuts[0], ElementType::i64); + auto shapeOfOp1 = std::make_shared(params[0], ElementType::i64); shapeOfOp1->set_friendly_name("shapeof1"); std::vector reduce_axes = {0}; auto reduceAxesNode = std::dynamic_pointer_cast( diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_with_empty_tensor.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_with_empty_tensor.cpp index 448c629d1a5..cd0bad894d3 100644 --- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_with_empty_tensor.cpp +++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/dynamic_smoke_test_with_empty_tensor.cpp @@ -91,19 +91,17 @@ protected: const auto AllZeroData = inputDynamicShapes[0]; const auto ConcatInputData = inputDynamicShapes[1]; ov::ParameterVector params; - for (auto&& shape : {AllZeroData, ConcatInputData}) { + for (auto&& shape : {AllZeroData, ConcatInputData}) params.push_back(std::make_shared(netType, shape)); - } - auto paramOuts = - helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); + const ElementType intInputsPrecision = ElementType::i32; - auto nonzeroEmptyResultOp = std::make_shared(paramOuts[0]); + auto nonzeroEmptyResultOp = std::make_shared(params[0]); auto convertEmptyInputOp = ngraph::builder::makeConversion(nonzeroEmptyResultOp, ElementType::i32, ngraph::helpers::ConversionTypes::CONVERT); auto concatPartialInputEmptyOp = - ngraph::builder::makeConcat({convertEmptyInputOp, paramOuts[1], convertEmptyInputOp}, + ngraph::builder::makeConcat({convertEmptyInputOp, params[1], convertEmptyInputOp}, 1); // partially empty input / non empty output auto concatEmptyInputEmptyOutputOp = ngraph::builder::makeConcat({convertEmptyInputOp, convertEmptyInputOp, convertEmptyInputOp}, @@ -117,14 +115,14 @@ protected: auto axisNode = ngraph::builder::makeConstant(intInputsPrecision, ov::Shape({1}), {0}); auto gatherEmptyIndicesOp = - std::make_shared(paramOuts[0], squeezeEmptyInputOp, axisNode, 0); + std::make_shared(params[0], squeezeEmptyInputOp, axisNode, 0); auto shapeofEmptyInputOp = std::make_shared(gatherEmptyIndicesOp, ElementType::i32); ngraph::ResultVector results = {std::make_shared(shapeofEmptyInputOp), std::make_shared(concatPartialInputEmptyOp), std::make_shared(concatEmptyInputEmptyOutputOp)}; function = std::make_shared(results, params, "result"); - auto nonzero = std::make_shared(paramOuts[0]); + auto nonzero = std::make_shared(params[0]); } }; diff --git a/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp b/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp index 05328c6b5fb..c57017666bd 100644 --- a/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp +++ b/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp @@ -1604,11 +1604,8 @@ std::shared_ptr generateMultiSubGraph(const std::shared_ptr generate(const std::shared_ptr &node) { ov::ParameterVector params{std::make_shared(ov::element::f32, ov::Shape{{1, 2, 4}}), std::make_shared(ov::element::f32, ov::Shape{{1, 2, 2}})}; - - const auto outputs = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); const auto nms = - std::make_shared(outputs[0], outputs[1], ov::op::v8::MatrixNms::Attributes()); + std::make_shared(params[0], params[1], ov::op::v8::MatrixNms::Attributes()); ov::ResultVector results{std::make_shared(nms)}; return std::make_shared(results, params, "MatrixNms"); } @@ -1616,14 +1613,12 @@ std::shared_ptr generate(const std::shared_ptr std::shared_ptr generateMulticlassNmsBase(const std::shared_ptr &node) { ov::ParameterVector params{std::make_shared(ov::element::f32, ov::Shape{{1, 2, 4}}), std::make_shared(ov::element::f32, ov::Shape{{1, 2, 2}})}; - const auto outputs = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); if (ov::is_type(node)) { - const auto nms = std::make_shared(outputs[0], outputs[1], ov::op::v8::MulticlassNms::Attributes()); + const auto nms = std::make_shared(params[0], params[1], ov::op::v8::MulticlassNms::Attributes()); ov::ResultVector results{std::make_shared(nms)}; return std::make_shared(results, params, "MulticlassNms"); } else if (ov::is_type(node)) { - const auto nms = std::make_shared(outputs[0], outputs[1], ov::op::v9::MulticlassNms::Attributes()); + const auto nms = std::make_shared(params[0], params[1], ov::op::v9::MulticlassNms::Attributes()); ov::ResultVector results{std::make_shared(nms)}; return std::make_shared(results, params, "MulticlassNms"); } else { @@ -1808,8 +1803,6 @@ std::shared_ptr generate(const std::shared_ptr(ov::element::f32, ov::Shape{{2, 2, 3, 4}}), std::make_shared(ov::element::f32, ov::Shape{{1, 12, 2, 2}}), std::make_shared(ov::element::f32, ov::Shape{{1, 3, 2, 2}})}; - const auto outputs = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); ov::op::v9::GenerateProposals::Attributes attrs; attrs.min_size = 1; attrs.nms_threshold = 0.8; @@ -1817,7 +1810,7 @@ std::shared_ptr generate(const std::shared_ptr(node)) { const auto gp = std::make_shared( - outputs[0], outputs[1], outputs[2], outputs[3], attrs); + params[0], params[1], params[2], params[3], attrs); ov::ResultVector results{std::make_shared(gp)}; return std::make_shared(results, params, "GenerateProposalsGraph"); } else { diff --git a/src/tests/functional/plugin/shared/include/behavior/plugin/preprocessing.hpp b/src/tests/functional/plugin/shared/include/behavior/plugin/preprocessing.hpp index 4d82286103e..aaf35c28aae 100644 --- a/src/tests/functional/plugin/shared/include/behavior/plugin/preprocessing.hpp +++ b/src/tests/functional/plugin/shared/include/behavior/plugin/preprocessing.hpp @@ -87,15 +87,14 @@ public: auto make_ngraph = [&](bool with_extra_conv) { auto in_prec = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(with_extra_conv ? inPrc : decltype(inPrc)(InferenceEngine::Precision::FP32)); ov::ParameterVector paramsIn {std::make_shared(in_prec, ov::Shape(inputShape))}; - auto paramIn = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(paramsIn)); - auto toF32 = std::make_shared(paramIn[0], ngraph::element::Type_t::f32); + auto toF32 = std::make_shared(paramsIn[0], ngraph::element::Type_t::f32); auto constNode = std::make_shared( ngraph::element::Type_t::i64, ngraph::Shape{inputShape.size()}, inputShape); + std::shared_ptr reshape_input = with_extra_conv ? toF32->shared_from_this() : paramsIn[0]; auto reshape = std::dynamic_pointer_cast( - std::make_shared(with_extra_conv ? toF32 : paramIn[0], constNode, specialZero)); + std::make_shared(reshape_input, constNode, specialZero)); ngraph::ResultVector results{std::make_shared(reshape)}; return std::make_shared(results, paramsIn, "Reshape"); }; diff --git a/src/tests/functional/plugin/shared/src/behavior/infer_request/set_io_blob_precision.cpp b/src/tests/functional/plugin/shared/src/behavior/infer_request/set_io_blob_precision.cpp index 212bfded16a..b938ecea564 100644 --- a/src/tests/functional/plugin/shared/src/behavior/infer_request/set_io_blob_precision.cpp +++ b/src/tests/functional/plugin/shared/src/behavior/infer_request/set_io_blob_precision.cpp @@ -105,9 +105,8 @@ void SetBlobTest::SetUp() { auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(precNg); ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape(IS))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto axisNode = std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape{}, std::vector{-1})->output(0); - auto cumSum = std::dynamic_pointer_cast(ngraph::builder::makeCumSum(paramOuts[0], axisNode, false, false)); + auto cumSum = std::dynamic_pointer_cast(ngraph::builder::makeCumSum(params[0], axisNode, false, false)); ngraph::ResultVector results{std::make_shared(cumSum)}; function = std::make_shared(results, params, "InferSetBlob"); } diff --git a/src/tests/functional/plugin/shared/src/single_layer_tests/invalid_cases/proposal.cpp b/src/tests/functional/plugin/shared/src/single_layer_tests/invalid_cases/proposal.cpp index ac697f1f1ac..19e014e4090 100644 --- a/src/tests/functional/plugin/shared/src/single_layer_tests/invalid_cases/proposal.cpp +++ b/src/tests/functional/plugin/shared/src/single_layer_tests/invalid_cases/proposal.cpp @@ -73,10 +73,9 @@ void ProposalBehTest::SetUp() { std::make_shared(ngPrc, ov::Shape(boxesShape))}; params[0]->set_friendly_name("scores"); params[1]->set_friendly_name("boxes"); - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); auto proposal = std::dynamic_pointer_cast( - ngraph::builder::makeProposal(paramOuts[0], paramOuts[1], img_info, ngPrc, + ngraph::builder::makeProposal(params[0], params[1], img_info, ngPrc, base_size, pre_nms_topn, post_nms_topn, diff --git a/src/tests/functional/shared_test_classes/src/subgraph/clamp_fq.cpp b/src/tests/functional/shared_test_classes/src/subgraph/clamp_fq.cpp index af9652a4c38..b8dfc25f12f 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/clamp_fq.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/clamp_fq.cpp @@ -62,9 +62,8 @@ namespace SubgraphTestsDefinitions { } auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); - auto clamp = std::make_shared(paramOuts[0], clamp_min_max[0], clamp_min_max[1]); + auto clamp = std::make_shared(params[0], clamp_min_max[0], clamp_min_max[1]); auto FQNode = ngraph::builder::makeFakeQuantize(clamp, ngraph::element::f32, levels[0], constShape[0], { inputDataMin }, { inputDataMax }, { inputDataMin }, { inputDataMax }); diff --git a/src/tests/functional/shared_test_classes/src/subgraph/convolution_relu_sequence.cpp b/src/tests/functional/shared_test_classes/src/subgraph/convolution_relu_sequence.cpp index c0e7fb730f3..b3f0c42713c 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/convolution_relu_sequence.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/convolution_relu_sequence.cpp @@ -49,7 +49,7 @@ void ConvolutionReluSequenceTest::SetUp() { configuration.insert(config.begin(), config.end()); auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape(convParamsAll.inputShape))}; - auto lastOutputs = ngraph::helpers::castOps2Nodes(params).front(); + std::shared_ptr lastOutputs = params.front(); auto inputChannels = convParamsAll.inputShape[1]; for (auto&& single : convParamsAll.sequenceDesc) { diff --git a/src/tests/functional/shared_test_classes/src/subgraph/multiply_add.cpp b/src/tests/functional/shared_test_classes/src/subgraph/multiply_add.cpp index dfc1dcdb5f7..02dbd4ef465 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/multiply_add.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/multiply_add.cpp @@ -28,14 +28,12 @@ void MultiplyAddLayerTest::SetUp() { ov::element::Type element_type; std::tie(inputShape, element_type, targetDevice) = this->GetParam(); ov::ParameterVector params{std::make_shared(element_type, ov::PartialShape(inputShape))}; - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector constShape(inputShape.size(), 1); constShape[1] = inputShape[1]; auto const_mul = ngraph::builder::makeConstant(element_type, constShape, {}, true); - auto mul = std::make_shared(paramOuts[0], const_mul); + auto mul = std::make_shared(params[0], const_mul); auto const_add = ngraph::builder::makeConstant(element_type, constShape, {}, true); auto add = std::make_shared(mul, const_add); ov::ResultVector results{std::make_shared(add)}; diff --git a/src/tests/functional/shared_test_classes/src/subgraph/mvn_multiply_add.cpp b/src/tests/functional/shared_test_classes/src/subgraph/mvn_multiply_add.cpp index 9ff6272b9ab..78d572cafd1 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/mvn_multiply_add.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/mvn_multiply_add.cpp @@ -46,10 +46,8 @@ void MVNMultiplyAdd::SetUp() { std::tie(inputShapes, constantShapes) = shapes; ov::ParameterVector param{std::make_shared(dataType, ov::Shape(inputShapes))}; - auto paramOuts = - ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(param)); auto axesNode = ngraph::builder::makeConstant(axesType, ov::Shape{axes.size()}, axes); - auto mvn = ngraph::builder::makeMVN6(paramOuts[0], axesNode, normalizeVariance, eps, epsMode); + auto mvn = ngraph::builder::makeMVN6(param[0], axesNode, normalizeVariance, eps, epsMode); auto gamma = ngraph::builder::makeConstant(dataType, constantShapes, {}, true); auto mul = std::make_shared(mvn, gamma); auto beta = ngraph::builder::makeConstant(dataType, constantShapes, {}, true); diff --git a/src/tests/functional/shared_test_classes/src/subgraph/quantized_convolution_backprop_data.cpp b/src/tests/functional/shared_test_classes/src/subgraph/quantized_convolution_backprop_data.cpp index 9f872e524d1..e9fd7e7f837 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/quantized_convolution_backprop_data.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/quantized_convolution_backprop_data.cpp @@ -53,12 +53,11 @@ void QuantConvBackpropDataLayerTest::SetUp() { std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType, quantLevels, quantGranularity) = groupConvBackpropDataParams; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector dataFqConstShapes(inputShape.size(), 1); if (quantGranularity == ngraph::helpers::Perchannel) dataFqConstShapes[1] = inputShape[1]; - auto dataFq = ngraph::builder::makeFakeQuantize(paramOuts[0], ngPrc, quantLevels, dataFqConstShapes); + auto dataFq = ngraph::builder::makeFakeQuantize(params[0], ngPrc, quantLevels, dataFqConstShapes); std::vector weightsShapes = {inputShape[1], convOutChannels}; weightsShapes.insert(weightsShapes.end(), kernel.begin(), kernel.end()); diff --git a/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution.cpp b/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution.cpp index 3ad85f760d2..1f9a505e83f 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution.cpp @@ -58,12 +58,11 @@ void QuantGroupConvLayerTest::SetUp() { std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, numGroups, quantLevels, quantGranularity, quantizeWeights) = groupConvParams; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector dataFqConstShapes(inputShape.size(), 1); if (quantGranularity == ngraph::helpers::Perchannel) dataFqConstShapes[1] = inputShape[1]; - auto dataFq = ngraph::builder::makeFakeQuantize(paramOuts[0], ngPrc, quantLevels, dataFqConstShapes); + auto dataFq = ngraph::builder::makeFakeQuantize(params[0], ngPrc, quantLevels, dataFqConstShapes); std::vector weightsShapes = {convOutChannels, inputShape[1]}; if (weightsShapes[0] % numGroups || weightsShapes[1] % numGroups) diff --git a/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution_backprop_data.cpp b/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution_backprop_data.cpp index 9e028c745b7..42022f1ec48 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution_backprop_data.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/quantized_group_convolution_backprop_data.cpp @@ -54,12 +54,11 @@ void QuantGroupConvBackpropDataLayerTest::SetUp() { std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, numGroups, padType, quantLevels, quantGranularity) = groupConvBackpropDataParams; auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); std::vector dataFqConstShapes(inputShape.size(), 1); if (quantGranularity == ngraph::helpers::Perchannel) dataFqConstShapes[1] = inputShape[1]; - auto dataFq = ngraph::builder::makeFakeQuantize(paramOuts[0], ngPrc, quantLevels, dataFqConstShapes); + auto dataFq = ngraph::builder::makeFakeQuantize(params[0], ngPrc, quantLevels, dataFqConstShapes); std::vector weightsShapes = {inputShape[1], convOutChannels}; if (weightsShapes[0] % numGroups || weightsShapes[1] % numGroups) diff --git a/src/tests/functional/shared_test_classes/src/subgraph/quantized_mat_mul.cpp b/src/tests/functional/shared_test_classes/src/subgraph/quantized_mat_mul.cpp index d4dae9e9e86..77413c4f8ab 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/quantized_mat_mul.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/quantized_mat_mul.cpp @@ -73,8 +73,6 @@ void QuantMatMulTest::SetUp() { auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape(inputShape0)), std::make_shared(ngPrc, ov::Shape(inputShape1))}; - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); auto makeFakeQuantizeNode = [ngPrc](size_t quantLevels, QuantRange inputRange, QuantRange outputRange, QuantizationGranularity quantGranularity, const ngraph::Output &in, std::vector inputShape, @@ -93,8 +91,8 @@ void QuantMatMulTest::SetUp() { return ngraph::builder::makeFakeQuantize(in, ngPrc, quantLevels, dataFqConstShapes, inputLowData, inputHighData, outputLowData, outputHighData); }; - auto dataFq0 = makeFakeQuantizeNode(quantLevels0, inputRange0, outputRange0, quantGranularity0, paramOuts[0], inputShape0, fqPrec0); - auto dataFq1 = makeFakeQuantizeNode(quantLevels1, inputRange1, outputRange1, quantGranularity1, paramOuts[1], inputShape1, fqPrec1); + auto dataFq0 = makeFakeQuantizeNode(quantLevels0, inputRange0, outputRange0, quantGranularity0, params[0], inputShape0, fqPrec0); + auto dataFq1 = makeFakeQuantizeNode(quantLevels1, inputRange1, outputRange1, quantGranularity1, params[1], inputShape1, fqPrec1); auto MatMul = std::dynamic_pointer_cast( ngraph::builder::makeMatMul(dataFq0, dataFq1)); diff --git a/src/tests/functional/shared_test_classes/src/subgraph/reduce_eltwise.cpp b/src/tests/functional/shared_test_classes/src/subgraph/reduce_eltwise.cpp index 99066cc4456..4c8dbd44e04 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/reduce_eltwise.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/reduce_eltwise.cpp @@ -34,8 +34,6 @@ void ReduceEltwiseTest::SetUp() { std::tie(inputShape, axes, opType, keepDims, netPrecision, targetDevice) = this->GetParam(); auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); std::vector shapeAxes; switch (opType) { @@ -54,7 +52,7 @@ void ReduceEltwiseTest::SetUp() { auto reductionAxesNode = std::dynamic_pointer_cast( std::make_shared(ngraph::element::Type_t::i64, ngraph::Shape(shapeAxes), axes)); - auto reduce = std::make_shared(paramOuts[0], reductionAxesNode, keepDims); + auto reduce = std::make_shared(params[0], reductionAxesNode, keepDims); std::vector constShape(reduce.get()->get_output_partial_shape(0).rank().get_length(), 1); ASSERT_GT(constShape.size(), 2); diff --git a/src/tests/functional/shared_test_classes/src/subgraph/strided_slice.cpp b/src/tests/functional/shared_test_classes/src/subgraph/strided_slice.cpp index 51593c0adff..fb2050287e6 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/strided_slice.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/strided_slice.cpp @@ -47,9 +47,7 @@ void StridedSliceTest::SetUp() { auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params {std::make_shared(ngPrc, ov::Shape(ssParams.inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector( - ngraph::helpers::castOps2Nodes(params)); - auto relu = std::make_shared(paramOuts[0]); + auto relu = std::make_shared(params[0]); auto ss = ngraph::builder::makeStridedSlice(relu, ssParams.begin, ssParams.end, ssParams.strides, ngPrc, ssParams.beginMask, ssParams.endMask, ssParams.newAxisMask, ssParams.shrinkAxisMask, ssParams.ellipsisAxisMask); ngraph::ResultVector results{std::make_shared(ss)}; diff --git a/src/tests/functional/shared_test_classes/src/subgraph/two_fake_quantize_to_fullyconnected.cpp b/src/tests/functional/shared_test_classes/src/subgraph/two_fake_quantize_to_fullyconnected.cpp index 80d23fd4e71..7fa90952ec1 100644 --- a/src/tests/functional/shared_test_classes/src/subgraph/two_fake_quantize_to_fullyconnected.cpp +++ b/src/tests/functional/shared_test_classes/src/subgraph/two_fake_quantize_to_fullyconnected.cpp @@ -65,7 +65,6 @@ void FakeQuantizeSubgraphTest::SetUp() { } auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision); ov::ParameterVector params{std::make_shared(ngPrc, ov::Shape(inputShape))}; - auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes(params)); const int seed = 0; std::mt19937 gen(seed); @@ -114,7 +113,7 @@ void FakeQuantizeSubgraphTest::SetUp() { auto lowNode = ngraph::builder::makeConstant(ngraph::element::f32, channelDataSize, inputMinRange, false); auto highNode = ngraph::builder::makeConstant(ngraph::element::f32, channelDataSize, inputMaxRange, false); - auto inputFQNode = ngraph::builder::makeFakeQuantize(paramOuts[0], ngraph::element::f32, levels[0], constShape[0], + auto inputFQNode = ngraph::builder::makeFakeQuantize(params[0], ngraph::element::f32, levels[0], constShape[0], { inputDataMin }, { inputDataMax }, { inputDataMin }, { inputDataMax }); auto weightsFQNode = std::make_shared(const_param,