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Clean up of tests/ov_helpers leftovers #21416

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merged 17 commits into from
Dec 13, 2023
Merged

Clean up of tests/ov_helpers leftovers #21416

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cf5fba1
CLean up ov_helpers headers from ngraph/
vurusovs Nov 30, 2023
6bf9ecf
Move `ngraph/` includes from ov_helpers to tests
vurusovs Dec 1, 2023
eaa26fc
Remove include of all opsets in builders.hpp
vurusovs Dec 1, 2023
a2ee07c
Remove opsets includes from ov_helpers
vurusovs Dec 1, 2023
1b73754
Fix GNA tests
vurusovs Dec 1, 2023
529d747
Delete comments
vurusovs Dec 1, 2023
b794957
ClangFormat
vurusovs Dec 1, 2023
80a670f
Merge branch 'master' into vu/ov_helpers_leftovers
vurusovs Dec 5, 2023
7de9901
Fix build
vurusovs Dec 5, 2023
b541fa1
Fix `-fpermissive`
vurusovs Dec 5, 2023
6b6c0a4
Fix build #2
vurusovs Dec 5, 2023
f30e441
Fix `<` && `>` in includes
vurusovs Dec 5, 2023
f73f928
Fix build #3
vurusovs Dec 5, 2023
3b78f36
Merge branch 'master' into vu/ov_helpers_leftovers
vurusovs Dec 6, 2023
72ecef3
Merge branch 'master' into vu/ov_helpers_leftovers
vurusovs Dec 12, 2023
b85980e
Build fix
vurusovs Dec 13, 2023
01716f2
Merge branch 'master' into vu/ov_helpers_leftovers
vurusovs Dec 13, 2023
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6 changes: 3 additions & 3 deletions ...sts/functional/shared_tests_instances/behavior/ov_infer_request/infer_request_dynamic.cpp
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Expand Up @@ -24,13 +24,13 @@ std::shared_ptr<ngraph::Function> getFunction2() {

auto in2add = ngraph::builder::makeConstant(ngPrc, {1, 2, 1, 1}, std::vector<float>{}, true);
auto add = ngraph::builder::makeEltwise(split->output(0), in2add, ngraph::helpers::EltwiseTypes::ADD);
auto relu1 = std::make_shared<ngraph::opset1::Relu>(add);
auto relu1 = std::make_shared<ov::op::v0::Relu>(add);

auto in2mult = ngraph::builder::makeConstant(ngPrc, {1, 2, 1, 1}, std::vector<float>{}, true);
auto mult = ngraph::builder::makeEltwise(split->output(1), in2mult, ngraph::helpers::EltwiseTypes::MULTIPLY);
auto relu2 = std::make_shared<ngraph::opset1::Relu>(mult);
auto relu2 = std::make_shared<ov::op::v0::Relu>(mult);

auto concat = std::make_shared<ngraph::opset1::Concat>(ngraph::OutputVector{relu1->output(0), relu2->output(0)}, 3);
auto concat = std::make_shared<ov::op::v0::Concat>(ngraph::OutputVector{relu1->output(0), relu2->output(0)}, 3);
concat->get_output_tensor(0).set_names({"concat"});

return std::make_shared<ngraph::Function>(concat, params, "SplitAddConcat");
Expand Down
10 changes: 5 additions & 5 deletions ...sts/functional/shared_tests_instances/behavior/ov_infer_request/infer_request_dynamic.cpp
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Expand Up @@ -29,9 +29,9 @@ std::shared_ptr<ngraph::Function> getFunction1() {

auto in2add = ngraph::builder::makeConstant(ngPrc, {1, 4, 1, 1}, std::vector<float>{}, true);
auto add = ngraph::builder::makeEltwise(params[0], in2add, ngraph::helpers::EltwiseTypes::ADD);
auto relu1 = std::make_shared<ngraph::opset1::Relu>(add->output(0));
auto relu1 = std::make_shared<ov::op::v0::Relu>(add->output(0));
relu1->get_output_tensor(0).set_names({"relu1"});
auto relu2 = std::make_shared<ngraph::opset1::Relu>(add->output(0));
auto relu2 = std::make_shared<ov::op::v0::Relu>(add->output(0));
relu2->get_output_tensor(0).set_names({"relu2"});

ngraph::NodeVector results{relu1, relu2};
Expand All @@ -51,13 +51,13 @@ std::shared_ptr<ngraph::Function> getFunction2() {

auto in2add = ngraph::builder::makeConstant(ngPrc, {1, 2, 1, 1}, std::vector<float>{}, true);
auto add = ngraph::builder::makeEltwise(split->output(0), in2add, ngraph::helpers::EltwiseTypes::ADD);
auto relu1 = std::make_shared<ngraph::opset1::Relu>(add);
auto relu1 = std::make_shared<ov::op::v0::Relu>(add);

auto in2mult = ngraph::builder::makeConstant(ngPrc, {1, 2, 1, 1}, std::vector<float>{}, true);
auto mult = ngraph::builder::makeEltwise(split->output(1), in2mult, ngraph::helpers::EltwiseTypes::MULTIPLY);
auto relu2 = std::make_shared<ngraph::opset1::Relu>(mult);
auto relu2 = std::make_shared<ov::op::v0::Relu>(mult);

auto concat = std::make_shared<ngraph::opset1::Concat>(ngraph::OutputVector{relu1->output(0), relu2->output(0)}, 3);
auto concat = std::make_shared<ov::op::v0::Concat>(ngraph::OutputVector{relu1->output(0), relu2->output(0)}, 3);
concat->get_output_tensor(0).set_names({"concat"});

return std::make_shared<ngraph::Function>(concat, params, "SplitAddConcat");
Expand Down
26 changes: 13 additions & 13 deletions ...ugins/intel_cpu/tests/functional/shared_tests_instances/behavior/plugin/caching_tests.cpp
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Expand Up @@ -40,37 +40,37 @@ namespace {
};

static std::shared_ptr<ngraph::Function> simple_function_non_max_suppression_internal(ngraph::element::Type, size_t) {
auto boxes = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 1000, 4});
auto scores = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 1, 1000});
auto max_output_boxes_per_class = opset1::Constant::create(element::i32, Shape{1}, {10});
auto iou_threshold = opset1::Constant::create(element::f32, Shape{1}, {0.75});
auto score_threshold = opset1::Constant::create(element::f32, Shape{1}, {0.7});
auto boxes = std::make_shared<ov::op::v0::Parameter>(element::f32, Shape{1, 1000, 4});
auto scores = std::make_shared<ov::op::v0::Parameter>(element::f32, Shape{1, 1, 1000});
auto max_output_boxes_per_class = ov::op::v0::Constant::create(element::i32, Shape{1}, {10});
auto iou_threshold = ov::op::v0::Constant::create(element::f32, Shape{1}, {0.75});
auto score_threshold = ov::op::v0::Constant::create(element::f32, Shape{1}, {0.7});
auto nms = std::make_shared<ov::op::internal::NonMaxSuppressionIEInternal>(boxes, scores, max_output_boxes_per_class,
iou_threshold, score_threshold, 0, true, element::i32);
auto res = std::make_shared<ngraph::opset6::Result>(nms);
auto res = std::make_shared<ov::op::v0::Result>(nms);
auto func = std::make_shared<Function>(NodeVector{nms}, ParameterVector{boxes, scores});
return func;
}

static std::shared_ptr<ngraph::Function> simple_function_matrix_nms_internal(ngraph::element::Type, size_t) {
auto boxes = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 1000, 4});
auto scores = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 1, 1000});
auto boxes = std::make_shared<ov::op::v0::Parameter>(element::f32, Shape{1, 1000, 4});
auto scores = std::make_shared<ov::op::v0::Parameter>(element::f32, Shape{1, 1, 1000});
ov::op::v8::MatrixNms::Attributes attr;
// convert_precision does not support internal op 'NmsStaticShapeIE'
attr.output_type = element::i32;
auto nms = std::make_shared<ov::op::internal::NmsStaticShapeIE<ov::op::v8::MatrixNms>>(boxes, scores, attr);
auto res = std::make_shared<ngraph::opset6::Result>(nms);
auto res = std::make_shared<ov::op::v0::Result>(nms);
auto func = std::make_shared<Function>(NodeVector{nms}, ParameterVector{boxes, scores});
return func;
}

static std::shared_ptr<ngraph::Function> simple_function_multiclass_nms_internal(ngraph::element::Type, size_t) {
auto boxes = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 1000, 4});
auto scores = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 1, 1000});
op::util::MulticlassNmsBase::Attributes attr;
auto boxes = std::make_shared<ov::op::v0::Parameter>(element::f32, Shape{1, 1000, 4});
auto scores = std::make_shared<ov::op::v0::Parameter>(element::f32, Shape{1, 1, 1000});
ov::op::util::MulticlassNmsBase::Attributes attr;
attr.output_type = element::i32;
auto nms = std::make_shared<ov::op::internal::MulticlassNmsIEInternal>(boxes, scores, attr);
auto res = std::make_shared<ngraph::opset6::Result>(nms);
auto res = std::make_shared<ov::op::v0::Result>(nms);
auto func = std::make_shared<Function>(NodeVector{nms}, ParameterVector{boxes, scores});
return func;
}
Expand Down
2 changes: 1 addition & 1 deletion ...ns/intel_cpu/tests/functional/shared_tests_instances/execution_graph_tests/add_output.cpp
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Expand Up @@ -18,7 +18,7 @@ inline InferenceEngine::CNNNetwork getTargetNetwork() {
auto input = std::make_shared<op::v0::Parameter>(type, shape);
auto mem_i = std::make_shared<op::v0::Constant>(type, shape, 0);
auto mem_r = std::make_shared<op::v3::ReadValue>(mem_i, "id");
auto mul = std::make_shared<ngraph::op::v1::Multiply>(mem_r, input);
auto mul = std::make_shared<ov::op::v1::Multiply>(mem_r, input);
auto mem_w = std::make_shared<op::v3::Assign>(mul, "id");
auto sigm = std::make_shared<ngraph::op::Sigmoid>(mul);
mem_r->set_friendly_name("Memory");
Expand Down
2 changes: 1 addition & 1 deletion ...functional/shared_tests_instances/low_precision_transformations/concat_transformation.cpp
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Expand Up @@ -108,7 +108,7 @@ const std::vector<ConcatTransformationTestValues> testValues = {
{},
{ 256ul, ngraph::Shape({}), {0.f}, {2.55f}, {0.f}, {2.55f} },
{},
std::make_shared<ngraph::opset1::Constant>(ov::element::u8, ov::Shape{1, 3, 16, 16}, std::vector<float>(3 * 16 * 16, 1.0)),
std::make_shared<ov::op::v0::Constant>(ov::element::u8, ov::Shape{1, 3, 16, 16}, std::vector<float>(3 * 16 * 16, 1.0)),
{},
{
{ ov::element::f16 },
Expand Down
7 changes: 3 additions & 4 deletions ...al/shared_tests_instances/low_precision_transformations/depth_to_space_transformation.cpp
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Expand Up @@ -9,17 +9,16 @@

using namespace LayerTestsDefinitions;
using namespace InferenceEngine::details;
using namespace ngraph::opset1;

namespace {
const std::vector<ngraph::element::Type> precisions = {
ngraph::element::f32,
// ngraph::element::f16
};

const std::vector<DepthToSpace::DepthToSpaceMode> modes = {
DepthToSpace::DepthToSpaceMode::BLOCKS_FIRST,
DepthToSpace::DepthToSpaceMode::DEPTH_FIRST
const std::vector<ov::op::v0::DepthToSpace::DepthToSpaceMode> modes = {
ov::op::v0::DepthToSpace::DepthToSpaceMode::BLOCKS_FIRST,
ov::op::v0::DepthToSpace::DepthToSpaceMode::DEPTH_FIRST
};

const std::vector<ngraph::PartialShape> inputShapesBS2 = {
Expand Down
6 changes: 3 additions & 3 deletions ...s/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/depth_to_space.cpp
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Expand Up @@ -15,9 +15,9 @@ const std::vector<ov::element::Type> model_types = {
ov::element::i16,
};

const std::vector<DepthToSpace::DepthToSpaceMode> modes = {
DepthToSpace::DepthToSpaceMode::BLOCKS_FIRST,
DepthToSpace::DepthToSpaceMode::DEPTH_FIRST
const std::vector<ov::op::v0::DepthToSpace::DepthToSpaceMode> modes = {
ov::op::v0::DepthToSpace::DepthToSpaceMode::BLOCKS_FIRST,
ov::op::v0::DepthToSpace::DepthToSpaceMode::DEPTH_FIRST
};

const std::vector<std::vector<ov::Shape>> input_shapes_bs2_static = {
Expand Down
40 changes: 20 additions & 20 deletions src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/convolution.cpp
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Expand Up @@ -28,7 +28,7 @@ std::string ConvolutionLayerCPUTest::getTestCaseName(const testing::TestParamInf
InputShape inputShape;
std::string targetDevice;
std::tie(convParams, netType, inType, outType, inputShape, targetDevice) = basicParamsSet;
ngraph::op::PadType padType;
ov::op::PadType padType;
InferenceEngine::SizeVector kernel, stride, dilation;
std::vector<ptrdiff_t> padBegin, padEnd;
size_t convOutChannels;
Expand Down Expand Up @@ -93,11 +93,11 @@ void ConvolutionLayerCPUTest::checkBiasFusing(ov::CompiledModel& execNet) const
ASSERT_TRUE(foundConv) << "Can't find Convolution node";
}

std::shared_ptr<ngraph::Node> ConvolutionLayerCPUTest::modifyGraph(const ngraph::element::Type& ngPrc,
ngraph::ParameterVector& params,
const std::shared_ptr<ngraph::Node>& lastNode) {
std::shared_ptr<ov::Node> ConvolutionLayerCPUTest::modifyGraph(const ov::element::Type& ngPrc,
ov::ParameterVector& params,
const std::shared_ptr<ov::Node>& lastNode) {
auto retNode = CpuTestWithFusing::modifyGraph(ngPrc, params, lastNode);
std::shared_ptr<ngraph::Node> opToShapeInfer = nullptr;
std::shared_ptr<ov::Node> opToShapeInfer = nullptr;
for (auto& targetShapes : targetStaticShapes) {
for (size_t i = targetShapes.size(); i < params.size(); ++i) {
const auto& shape = params[i]->get_output_partial_shape(0);
Expand All @@ -109,13 +109,13 @@ std::shared_ptr<ngraph::Node> ConvolutionLayerCPUTest::modifyGraph(const ngraph:
// operation, and it has to match the convolution output shape. So the most suitable solution here is to
// perform shape inference on the convolution node
if (!opToShapeInfer) {
ngraph::OutputVector inputsForShapeInfer;
ov::OutputVector inputsForShapeInfer;
for (size_t j = 0; j < lastNode->get_input_size(); j++) {
if (ngraph::is_type<ngraph::opset1::Constant>(lastNode->get_input_node_ptr(j))) {
if (ov::is_type<ov::op::v0::Constant>(lastNode->get_input_node_ptr(j))) {
inputsForShapeInfer.push_back(lastNode->get_input_node_shared_ptr(j));
} else {
inputsForShapeInfer.push_back(
std::make_shared<ngraph::opset1::Parameter>(lastNode->get_input_element_type(j),
std::make_shared<ov::op::v0::Parameter>(lastNode->get_input_element_type(j),
lastNode->get_input_partial_shape(j)));
}
}
Expand Down Expand Up @@ -169,7 +169,7 @@ void ConvolutionLayerCPUTest::SetUp() {
selectedType = makeSelectedTypeStr(selectedType, netType);
}

ngraph::op::PadType padType;
ov::op::PadType padType;
InferenceEngine::SizeVector stride;
std::vector<ptrdiff_t> padBegin, padEnd;
size_t convOutChannels;
Expand Down Expand Up @@ -636,7 +636,7 @@ const convParams_ExplicitPaddingType& convParams_ExplicitPadding_GEMM_2D() {
::testing::ValuesIn(padEnds2d()),
::testing::ValuesIn(dilations2d()),
::testing::ValuesIn(numOutChannels_Gemm()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_GEMM_2D;
}

Expand All @@ -648,7 +648,7 @@ const convParams_ExplicitPaddingDilatedType& convParams_ExplicitPadding_GEMM_2D_
::testing::ValuesIn(padEnds2d()),
::testing::Values(SizeVector{2, 2}),
::testing::ValuesIn(numOutChannels_Gemm()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_GEMM_2D_dilated;
}

Expand All @@ -660,7 +660,7 @@ const convParams_ExplicitPaddingType& convParams_ExplicitPadding_GEMM_1D() {
::testing::ValuesIn(padEnds1d()),
::testing::ValuesIn(dilations1d()),
::testing::ValuesIn(numOutChannels_Gemm()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_GEMM_1D;
}

Expand All @@ -672,7 +672,7 @@ const convParams_ExplicitPaddingType& convParams_ExplicitPadding_2D() {
::testing::ValuesIn(padEnds2d()),
::testing::ValuesIn(dilations2d()),
::testing::ValuesIn(numOutChannels()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_2D;
}

Expand All @@ -684,7 +684,7 @@ const convParams_ExplicitPaddingDilatedType& convParams_ExplicitPadding_2D_dilat
::testing::ValuesIn(padEnds2d()),
::testing::Values(SizeVector{2, 2}),
::testing::ValuesIn(numOutChannels()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_2D_dilated;
}

Expand All @@ -696,7 +696,7 @@ const convParams_ExplicitPaddingType& convParams_ExplicitPadding_GEMM_3D() {
::testing::ValuesIn(padEnds3d()),
::testing::ValuesIn(dilations3d()),
::testing::ValuesIn(numOutChannels_Gemm()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_GEMM_3D;
}

Expand All @@ -708,7 +708,7 @@ const convParams_ExplicitPaddingDilatedType& convParams_ExplicitPadding_GEMM_3D_
::testing::ValuesIn(padEnds3d()),
::testing::Values(SizeVector{2, 2, 2}),
::testing::ValuesIn(numOutChannels_Gemm()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_GEMM_3D_dilated;
}

Expand All @@ -720,7 +720,7 @@ const convParams_ExplicitPaddingType& convParams_ExplicitPadding_3D() {
::testing::ValuesIn(padEnds3d()),
::testing::ValuesIn(dilations3d()),
::testing::ValuesIn(numOutChannels()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_3D;
}

Expand All @@ -732,7 +732,7 @@ const convParams_ExplicitPaddingDilatedType& convParams_ExplicitPadding_3D_dilat
::testing::ValuesIn(padEnds3d()),
::testing::Values(SizeVector{2, 2, 2}),
::testing::ValuesIn(numOutChannels()),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_3D_dilated;
}

Expand All @@ -744,7 +744,7 @@ const convParams_ExplicitPadding_1x1_Type& convParams_ExplicitPadding_1x1_1D() {
::testing::Values(std::vector<ptrdiff_t>({0})),
::testing::Values(SizeVector({1})),
::testing::Values(63),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_1x1_1D;
}

Expand All @@ -756,7 +756,7 @@ const convParams_ExplicitPadding_1x1_Type& convParams_ExplicitPadding_1x1_2D() {
::testing::Values(std::vector<ptrdiff_t>({0, 0})),
::testing::Values(SizeVector({1, 1})),
::testing::Values(63),
::testing::Values(ngraph::op::PadType::EXPLICIT));
::testing::Values(ov::op::PadType::EXPLICIT));
return convParams_ExplicitPadding_1x1_2D;
}

Expand Down
4 changes: 2 additions & 2 deletions src/plugins/intel_cpu/tests/functional/single_layer_tests/convolution_backprop_data.cpp
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Expand Up @@ -150,11 +150,11 @@ class DeconvolutionLayerCPUTest : public testing::WithParamInterface<DeconvLayer
if (!outShapeData.empty()) {
if (outShapeType == ngraph::helpers::InputLayerType::PARAMETER) {
OPENVINO_ASSERT(inputDynamicShapes.size() == 2);
auto outShapeParam = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::i32, inputDynamicShapes.back());
auto outShapeParam = std::make_shared<ov::op::v0::Parameter>(ngraph::element::i32, inputDynamicShapes.back());
params.push_back(outShapeParam);
outShapeNode = outShapeParam;
} else {
outShapeNode = ngraph::opset8::Constant::create(ngraph::element::i32, {outShapeData[inferRequestNum].size()}, outShapeData[inferRequestNum]);
outShapeNode = ov::op::v0::Constant::create(ngraph::element::i32, {outShapeData[inferRequestNum].size()}, outShapeData[inferRequestNum]);
}
}

Expand Down
4 changes: 2 additions & 2 deletions src/plugins/intel_cpu/tests/functional/single_layer_tests/group_convolution.cpp
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Expand Up @@ -133,10 +133,10 @@ class GroupConvolutionLayerCPUTest : public testing::WithParamInterface<groupCon
if (!opToShapeInfer) {
ngraph::OutputVector inputsForShapeInfer;
for (size_t j = 0; j < lastNode->get_input_size(); j++) {
if (ngraph::is_type<ngraph::opset1::Constant>(lastNode->get_input_node_ptr(j))) {
if (ngraph::is_type<ov::op::v0::Constant>(lastNode->get_input_node_ptr(j))) {
inputsForShapeInfer.push_back(lastNode->get_input_node_shared_ptr(j));
} else {
inputsForShapeInfer.push_back(std::make_shared<ngraph::opset1::Parameter>(lastNode->get_input_element_type(j),
inputsForShapeInfer.push_back(std::make_shared<ov::op::v0::Parameter>(lastNode->get_input_element_type(j),
lastNode->get_input_partial_shape(j)));
}
}
Expand Down
4 changes: 2 additions & 2 deletions ...plugins/intel_cpu/tests/functional/single_layer_tests/group_convolution_backprop_data.cpp
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Expand Up @@ -168,11 +168,11 @@ class GroupDeconvolutionLayerCPUTest : public testing::WithParamInterface<GroupD
if (!outShapeData.empty()) {
if (outShapeType == ngraph::helpers::InputLayerType::PARAMETER) {
OPENVINO_ASSERT(inputDynamicShapes.size() == 2);
auto outShapeParam = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::i32, inputDynamicShapes.back());
auto outShapeParam = std::make_shared<ov::op::v0::Parameter>(ngraph::element::i32, inputDynamicShapes.back());
params.push_back(outShapeParam);
outShapeNode = outShapeParam;
} else {
outShapeNode = ngraph::opset8::Constant::create(ngraph::element::i32, {outShapeData[inferRequestNum].size()}, outShapeData[inferRequestNum]);
outShapeNode = ov::op::v0::Constant::create(ngraph::element::i32, {outShapeData[inferRequestNum].size()}, outShapeData[inferRequestNum]);
}
}

Expand Down
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