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Clean up of tests/ov_helpers leftovers (#21416)
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* CLean up ov_helpers headers from ngraph/

* Move `ngraph/` includes from ov_helpers to tests

* Remove include of all opsets in builders.hpp

* Remove opsets includes from ov_helpers

* Fix GNA tests

* Delete comments

* ClangFormat

* Fix build

* Fix `-fpermissive`

* Fix build #2

* Fix `<` && `>` in includes

* Fix build #3

* Build fix
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@vurusovs
vurusovs authored Dec 13, 2023
1 parent adb4703 commit dcf9247
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Showing 393 changed files with 3,551 additions and 3,642 deletions.
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");
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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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