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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");
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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");
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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;
}
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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");
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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 },
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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 = {
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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 = {
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4 changes: 2 additions & 2 deletions src/plugins/intel_cpu/tests/functional/single_layer_tests/psroi_pooling.cpp
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Expand Up @@ -89,13 +89,13 @@ class PSROIPoolingLayerCPUTest : public testing::WithParamInterface<PSROIPooling
auto coords = ngraph::builder::makeConstant<float>(ngraph::element::f32, proposalShape, proposal);
ov::ParameterVector params {std::make_shared<ov::op::v0::Parameter>(ngraph::element::f32, ov::Shape(featureMapShape))};

auto psroi = std::make_shared<ngraph::op::v0::PSROIPooling>(params[0], coords, outputDim, groupSize,
auto psroi = std::make_shared<ov::op::v0::PSROIPooling>(params[0], coords, outputDim, groupSize,
spatialScale, spatialBinsX, spatialBinsY, mode);
psroi->get_rt_info() = getCPUInfo();
selectedType = getPrimitiveType() + "_" + inPrc.name();

threshold = 1e-2f;
const ngraph::ResultVector results{std::make_shared<ngraph::opset3::Result>(psroi)};
const ngraph::ResultVector results{std::make_shared<ov::op::v0::Result>(psroi)};
function = std::make_shared<ngraph::Function>(results, params, "PSROIPooling");
}
};
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10 changes: 5 additions & 5 deletions src/plugins/intel_cpu/tests/functional/single_layer_tests/range.cpp
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Expand Up @@ -112,17 +112,17 @@
// step = std::get<2>(rangeInputs);
// auto ngOutPr = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(outPrc);
// auto ngNetPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(inPrc);
// auto startPar = std::make_shared<ngraph::opset5::Parameter>(ngNetPrc, ngraph::Shape{});
// auto stopPar = std::make_shared<ngraph::opset5::Parameter>(ngNetPrc, ngraph::Shape{});
// auto stepPar = std::make_shared<ngraph::opset5::Parameter>(ngNetPrc, ngraph::Shape{});
// auto range = std::make_shared<ngraph::opset4::Range>(startPar, stopPar, stepPar, ngOutPr);
// auto startPar = std::make_shared<ov::op::v0::Parameter>(ngNetPrc, ngraph::Shape{});
// auto stopPar = std::make_shared<ov::op::v0::Parameter>(ngNetPrc, ngraph::Shape{});
// auto stepPar = std::make_shared<ov::op::v0::Parameter>(ngNetPrc, ngraph::Shape{});
// auto range = std::make_shared<ov::op::v4::Range>(startPar, stopPar, stepPar, ngOutPr);
// range->get_rt_info() = getCPUInfo();
// selectedType = std::string("ref_any_") + (inPrc == outPrc ? inPrc.name() : "FP32");
// startPar->set_friendly_name("start");
// stopPar->set_friendly_name("stop");
// stepPar->set_friendly_name("step");
//
// const ngraph::ResultVector results{std::make_shared<ngraph::opset3::Result>(range)};
// const ngraph::ResultVector results{std::make_shared<ov::op::v0::Result>(range)};
// function = std::make_shared<ngraph::Function>(results, ngraph::ParameterVector {
// startPar, stopPar, stepPar}, "Range");
// functionRefs = ngraph::clone_function(*function);
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2 changes: 1 addition & 1 deletion src/plugins/intel_cpu/tests/functional/subgraph_tests/src/concat_sdp.cpp
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Expand Up @@ -102,7 +102,7 @@ class ConcatSDPTest : public testing::WithParamInterface<ConcatSDPTestParams>, v
auto concatV = std::make_shared<ov::op::v0::Concat>(OutputVector{pastv, inputParams[2]}, 2);
auto sdp = std::make_shared<ov::opset13::ScaledDotProductAttention>(inputParams[0], concatK, concatV, false);
sdp->set_friendly_name("mha");
auto add = std::make_shared<op::v1::Add>(sdp, op::v0::Constant::create(inType, {1}, {1.0f}));
auto add = std::make_shared<ov::op::v1::Add>(sdp, op::v0::Constant::create(inType, {1}, {1.0f}));
auto pastk_assign = std::make_shared<op::v6::Assign>(concatK, var_k);
auto pastv_assign = std::make_shared<op::v6::Assign>(concatV, var_v);
pastk_assign->set_friendly_name("pastk_w");
Expand Down
56 changes: 28 additions & 28 deletions src/plugins/intel_cpu/tests/functional/subgraph_tests/src/rotary_pos_emb.cpp
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Expand Up @@ -65,29 +65,29 @@ static std::shared_ptr<ov::Model> buildROPE_Llama2(const int batch,
auto Constant585 = cos_sin_cache[1];

// concat KV length
auto transpose_Transpose = makeOP<opset1::Transpose>({input, {0, 2, 1, 3}});
auto slice_Unsqueeze_426 = makeOP<opset1::Unsqueeze>({pos_id_end, 0});
auto ScatterUpdate_152236 = makeOP<opset3::ScatterUpdate>({{0, 0, 0}, {2}, slice_Unsqueeze_426, {0}});
auto slice_Slice = makeOP<opset1::StridedSlice>({Constant582, {0, 0, 0}, ScatterUpdate_152236, {1, 1, 1}},
auto transpose_Transpose = makeOP<ov::op::v1::Transpose>({input, {0, 2, 1, 3}});
auto slice_Unsqueeze_426 = makeOP<ov::op::v0::Unsqueeze>({pos_id_end, 0});
auto ScatterUpdate_152236 = makeOP<ov::op::v3::ScatterUpdate>({{0, 0, 0}, {2}, slice_Unsqueeze_426, {0}});
auto slice_Slice = makeOP<ov::op::v1::StridedSlice>({Constant582, {0, 0, 0}, ScatterUpdate_152236, {1, 1, 1}},
{{"begin_mask", {1, 1, 0}},
{"end_mask", {1, 1, 0}},
{"new_axis_mask", {}},
{"shrink_axis_mask", {}},
{"ellipsis_mask", {}}});
auto squeeze_Squeeze = makeOP<opset1::Squeeze>({slice_Slice, 1});
auto squeeze_Squeeze_435 = makeOP<opset1::Squeeze>({squeeze_Squeeze, 0});
auto index_441_Gather = makeOP<opset8::Gather>({squeeze_Squeeze_435, pos_ids, 0}, {{"batch_dims", 0}});
auto unsqueeze_Unsqueeze = makeOP<opset1::Unsqueeze>({index_441_Gather, 1});
auto squeeze_Squeeze = makeOP<ov::op::v0::Squeeze>({slice_Slice, 1});
auto squeeze_Squeeze_435 = makeOP<ov::op::v0::Squeeze>({squeeze_Squeeze, 0});
auto index_441_Gather = makeOP<ov::op::v8::Gather>({squeeze_Squeeze_435, pos_ids, 0}, {{"batch_dims", 0}});
auto unsqueeze_Unsqueeze = makeOP<ov::op::v0::Unsqueeze>({index_441_Gather, 1});
auto mul_Multiply =
makeOP<opset1::Multiply>({transpose_Transpose, unsqueeze_Unsqueeze}, {{"auto_broadcast", "numpy"}});
auto size_ShapeOf_448 = makeOP<opset3::ShapeOf>({transpose_Transpose}, {{"output_type", "i32"}});
auto size_Gather_450 = makeOP<opset8::Gather>({size_ShapeOf_448, 3, 0}, {{"batch_dims", 0}});
makeOP<ov::op::v1::Multiply>({transpose_Transpose, unsqueeze_Unsqueeze}, {{"auto_broadcast", "numpy"}});
auto size_ShapeOf_448 = makeOP<ov::op::v3::ShapeOf>({transpose_Transpose}, {{"output_type", "i32"}});
auto size_Gather_450 = makeOP<ov::op::v8::Gather>({size_ShapeOf_448, 3, 0}, {{"batch_dims", 0}});
auto floor_divide_Divide =
makeOP<opset1::Divide>({size_Gather_450, 2}, {{"auto_broadcast", "numpy"}, {"m_pythondiv", true}});
auto floor_divide_Floor = makeOP<opset1::Floor>({floor_divide_Divide});
auto slice_Unsqueeze_452 = makeOP<opset1::Unsqueeze>({floor_divide_Floor, 0});
auto ScatterUpdate_152312 = makeOP<opset3::ScatterUpdate>({{0, 0, 0, 0}, {3}, slice_Unsqueeze_452, {0}});
auto slice_Slice_459 = makeOP<opset1::StridedSlice>(
makeOP<ov::op::v1::Divide>({size_Gather_450, 2}, {{"auto_broadcast", "numpy"}, {"m_pythondiv", true}});
auto floor_divide_Floor = makeOP<ov::op::v0::Floor>({floor_divide_Divide});
auto slice_Unsqueeze_452 = makeOP<ov::op::v0::Unsqueeze>({floor_divide_Floor, 0});
auto ScatterUpdate_152312 = makeOP<ov::op::v3::ScatterUpdate>({{0, 0, 0, 0}, {3}, slice_Unsqueeze_452, {0}});
auto slice_Slice_459 = makeOP<ov::op::v1::StridedSlice>(
{transpose_Transpose, ScatterUpdate_152312, {0ll, 0ll, 0ll, LLONG_MAX}, {1, 1, 1, 1}},
{{"begin_mask", {1, 1, 1, 0}},
{"end_mask", {1, 1, 1, 0}},
Expand All @@ -102,30 +102,30 @@ static std::shared_ptr<ov::Model> buildROPE_Llama2(const int batch,
1,
}),
{-1.000000f});
auto neg_Multiply = makeOP<opset1::Multiply>({slice_Slice_459, Constant_182988}, {{"auto_broadcast", "numpy"}});
auto ScatterUpdate_152368 = makeOP<opset3::ScatterUpdate>({{0, 0, 0, 0}, {3}, slice_Unsqueeze_452, {0}});
auto neg_Multiply = makeOP<ov::op::v1::Multiply>({slice_Slice_459, Constant_182988}, {{"auto_broadcast", "numpy"}});
auto ScatterUpdate_152368 = makeOP<ov::op::v3::ScatterUpdate>({{0, 0, 0, 0}, {3}, slice_Unsqueeze_452, {0}});
auto slice_Slice2 =
makeOP<opset1::StridedSlice>({transpose_Transpose, {0, 0, 0, 0}, ScatterUpdate_152368, {1, 1, 1, 1}},
makeOP<ov::op::v1::StridedSlice>({transpose_Transpose, {0, 0, 0, 0}, ScatterUpdate_152368, {1, 1, 1, 1}},
{{"begin_mask", {1, 1, 1, 0}},
{"end_mask", {1, 1, 1, 0}},
{"new_axis_mask", {}},
{"shrink_axis_mask", {}},
{"ellipsis_mask", {}}});
auto cat_Concat = makeOP<opset1::Concat>({neg_Multiply, slice_Slice2}, {{"axis", -1}});
auto ScatterUpdate_152421 = makeOP<opset3::ScatterUpdate>({{0, 0, 0}, {2}, slice_Unsqueeze_426, {0}});
auto slice_Slice_433 = makeOP<opset1::StridedSlice>({Constant585, {0, 0, 0}, ScatterUpdate_152421, {1, 1, 1}},
auto cat_Concat = makeOP<ov::op::v0::Concat>({neg_Multiply, slice_Slice2}, {{"axis", -1}});
auto ScatterUpdate_152421 = makeOP<ov::op::v3::ScatterUpdate>({{0, 0, 0}, {2}, slice_Unsqueeze_426, {0}});
auto slice_Slice_433 = makeOP<ov::op::v1::StridedSlice>({Constant585, {0, 0, 0}, ScatterUpdate_152421, {1, 1, 1}},
{{"begin_mask", {1, 1, 0}},
{"end_mask", {1, 1, 0}},
{"new_axis_mask", {}},
{"shrink_axis_mask", {}},
{"ellipsis_mask", {}}});
auto squeeze_Squeeze_436 = makeOP<opset1::Squeeze>({slice_Slice_433, 1});
auto squeeze_Squeeze_437 = makeOP<opset1::Squeeze>({squeeze_Squeeze_436, 0});
auto index_446_Gather = makeOP<opset8::Gather>({squeeze_Squeeze_437, pos_ids, 0}, {{"batch_dims", 0}});
auto unsqueeze_Unsqueeze_447 = makeOP<opset1::Unsqueeze>({index_446_Gather, 1});
auto squeeze_Squeeze_436 = makeOP<ov::op::v0::Squeeze>({slice_Slice_433, 1});
auto squeeze_Squeeze_437 = makeOP<ov::op::v0::Squeeze>({squeeze_Squeeze_436, 0});
auto index_446_Gather = makeOP<ov::op::v8::Gather>({squeeze_Squeeze_437, pos_ids, 0}, {{"batch_dims", 0}});
auto unsqueeze_Unsqueeze_447 = makeOP<ov::op::v0::Unsqueeze>({index_446_Gather, 1});
auto mul_Multiply_463 =
makeOP<opset1::Multiply>({cat_Concat, unsqueeze_Unsqueeze_447}, {{"auto_broadcast", "numpy"}});
auto add_Add = makeOP<opset1::Add>({mul_Multiply, mul_Multiply_463}, {{"auto_broadcast", "numpy"}});
makeOP<ov::op::v1::Multiply>({cat_Concat, unsqueeze_Unsqueeze_447}, {{"auto_broadcast", "numpy"}});
auto add_Add = makeOP<ov::op::v1::Add>({mul_Multiply, mul_Multiply_463}, {{"auto_broadcast", "numpy"}});

return std::make_shared<ov::Model>(ov::NodeVector{add_Add}, ov::ParameterVector{input, pos_id_end, pos_ids});
}
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