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ngraph::opset -> ov::opset
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@vurusovs
vurusovs committed Dec 5, 2023
1 parent 4baa7ed commit 368db6d
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Showing 11 changed files with 29 additions and 29 deletions.
2 changes: 1 addition & 1 deletion modules/nvidia_plugin/src/transformer/nodes/fused_convolution_backprop_data.cpp
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Expand Up @@ -200,7 +200,7 @@ void FusedConvBackpropData::validate_and_infer_types() {
// If auto_pad has one of following mode we infer paddings. Otherwise in
// EXPLICIT auto_pad mode we use what is provided.
if (auto_pad_ == ov::op::PadType::SAME_UPPER || auto_pad_ == ov::op::PadType::SAME_LOWER) {
ngraph::opset1::infer_conv_backprop_auto_padding(
ov::opset1::infer_conv_backprop_auto_padding(
ov::Shape{std::next(data_shape.begin(), 2), std::end(data_shape)},
ov::Shape{std::next(filters_shape.begin(), 2), std::end(filters_shape)},
output_shape,
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6 changes: 3 additions & 3 deletions .../tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data.cpp
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Expand Up @@ -128,7 +128,7 @@ class ConvolutionBackpropDataExtendedLayerTest
const ov::op::PadType &autoPad,
bool addBiases = false,
const std::vector<float> &biasesWeights = {}) {
return std::make_shared<ngraph::opset1::ConvolutionBackpropData>(
return std::make_shared<ov::opset1::ConvolutionBackpropData>(
in, weights, output, strides, padsBegin, padsEnd, dilations, autoPad);
}

Expand Down Expand Up @@ -158,7 +158,7 @@ class ConvolutionBackpropDataExtendedLayerTest

auto outputShapeNode = std::make_shared<ov::op::v0::Constant>(
ov::element::Type_t::i64, ov::Shape{outputShapeData.size()}, outputShapeData);
auto convBackpropData = std::dynamic_pointer_cast<ngraph::opset1::ConvolutionBackpropData>(
auto convBackpropData = std::dynamic_pointer_cast<ov::opset1::ConvolutionBackpropData>(
makeConvolutionBackpropData(params[0],
outputShapeNode,
ngPrc,
Expand All @@ -169,7 +169,7 @@ class ConvolutionBackpropDataExtendedLayerTest
dilation,
padType,
convOutChannels));
ov::ResultVector results{std::make_shared<ngraph::opset1::Result>(convBackpropData)};
ov::ResultVector results{std::make_shared<ov::opset1::Result>(convBackpropData)};
function = std::make_shared<ngraph::Function>(results, params, "convolutionBackpropData");
}
};
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6 changes: 3 additions & 3 deletions ...ts/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data_add.cpp
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Expand Up @@ -126,7 +126,7 @@ class ConvolutionBackpropDataAddExtendedLayerTest
const ov::op::PadType &autoPad,
bool addBiases = false,
const std::vector<float> &biasesWeights = {}) {
return std::make_shared<ngraph::opset1::ConvolutionBackpropData>(
return std::make_shared<ov::opset1::ConvolutionBackpropData>(
in, weights, output, strides, padsBegin, padsEnd, dilations, autoPad);
}

Expand Down Expand Up @@ -156,7 +156,7 @@ class ConvolutionBackpropDataAddExtendedLayerTest

auto outputShapeNode = std::make_shared<ov::op::v0::Constant>(
ov::element::Type_t::i64, ov::Shape{outputShapeData.size()}, outputShapeData);
auto convBackpropData = std::dynamic_pointer_cast<ngraph::opset1::ConvolutionBackpropData>(
auto convBackpropData = std::dynamic_pointer_cast<ov::opset1::ConvolutionBackpropData>(
makeConvolutionBackpropData(params[0],
outputShapeNode,
ngPrc,
Expand All @@ -172,7 +172,7 @@ class ConvolutionBackpropDataAddExtendedLayerTest
ov::test::utils::fill_tensor_random(random_tensor);
auto addConstant = std::make_shared<ov::op::v0::Constant>(random_tensor);
auto add = std::make_shared<ov::op::v1::Add>(convBackpropData, addConstant);
ov::ResultVector results{std::make_shared<ngraph::opset1::Result>(add)};
ov::ResultVector results{std::make_shared<ov::opset1::Result>(add)};
function = std::make_shared<ngraph::Function>(results, params, "convolutionBackpropData");
}
};
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8 changes: 4 additions & 4 deletions ...s/functional/shared_tests_instances/single_layer_tests/convolution_biasadd_activation.hpp
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Expand Up @@ -50,7 +50,7 @@ struct ConvBAATraits {};

template <>
struct ConvBAATraits<ConvolutionLayerTest> {
using ConvNode = ngraph::opset1::Convolution;
using ConvNode = ov::opset1::Convolution;
using ConvParamSet = convLayerTestParamsSet;
using ConvSpecParamsSet = convSpecificParams;
using ConvBAAParamSet = convBAATestParamSet;
Expand All @@ -59,7 +59,7 @@ struct ConvBAATraits<ConvolutionLayerTest> {

template <>
struct ConvBAATraits<GroupConvolutionLayerTest> {
using ConvNode = ngraph::opset1::GroupConvolution;
using ConvNode = ov::opset1::GroupConvolution;
using ConvParamSet = groupConvLayerTestParamsSet;
using ConvSpecParamsSet = groupConvSpecificParams;
using ConvBAAParamSet = groupConvBAATestParamSet;
Expand Down Expand Up @@ -127,7 +127,7 @@ class BasicConvolutionBiasAddActivationLayerTest

std::shared_ptr<ov::Node> lastNode;
if constexpr (HasAddNode) {
auto addParam = std::make_shared<ngraph::opset1::Parameter>(ngNetPrc, convLayer->get_output_shape(0));
auto addParam = std::make_shared<ov::opset1::Parameter>(ngNetPrc, convLayer->get_output_shape(0));
params.push_back(addParam);
auto addLayer = std::make_shared<ov::op::v1::Add>(biasAddLayer, addParam);
lastNode = addLayer;
Expand All @@ -138,7 +138,7 @@ class BasicConvolutionBiasAddActivationLayerTest
lastNode = ngraph::builder::makeActivation(lastNode, ngNetPrc, activation);
}

ov::ResultVector results{std::make_shared<ngraph::opset1::Result>(lastNode)};
ov::ResultVector results{std::make_shared<ov::opset1::Result>(lastNode)};
function = std::make_shared<ngraph::Function>(results, params, Traits::name);
}

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4 changes: 2 additions & 2 deletions ...dia_plugin/tests/functional/shared_tests_instances/single_layer_tests/fully_connected.cpp
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Expand Up @@ -98,7 +98,7 @@ class FullyConnectedLayerTest : public testing::WithParamInterface<FullyConnecte
auto MatMul = std::make_shared<ov::op::v0::MatMul>(
params[0], secondaryInput, shapeRelatedParams.input1.second, shapeRelatedParams.input2.second);
auto Add = std::make_shared<ov::op::v1::Add>(MatMul, thirdInput);
ov::ResultVector results{std::make_shared<ngraph::opset1::Result>(Add)};
ov::ResultVector results{std::make_shared<ov::opset1::Result>(Add)};
function = std::make_shared<ngraph::Function>(results, params, "FullyConnected");
}
};
Expand Down Expand Up @@ -224,7 +224,7 @@ class FullyConnectedLayer2MatMulTest : public testing::WithParamInterface<FullyC
shapeRelatedParams.matmul2_input1.second,
shapeRelatedParams.matmul2_input2.second);
auto Add = std::make_shared<ov::op::v1::Add>(matMul0, matMul1);
ov::ResultVector results{std::make_shared<ngraph::opset1::Result>(Add)};
ov::ResultVector results{std::make_shared<ov::opset1::Result>(Add)};
function = std::make_shared<ngraph::Function>(results, params, "FullyConnected");
}
};
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2 changes: 1 addition & 1 deletion ...les/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp
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Expand Up @@ -34,7 +34,7 @@ class CUDNNGRUCellTest : public UnsymmetricalComparer<GRUCellTest> {
const auto& ops = function->get_ordered_ops();
int seed = SEED_FIRST;
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (std::dynamic_pointer_cast<ov::opset1::Constant>(op)) {
ov::Tensor random_tensor(op->get_element_type(), op->get_shape());
ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed++);
function->replace_node(op, std::make_shared<ov::op::v0::Constant>(random_tensor));
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8 changes: 4 additions & 4 deletions ...nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp
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Expand Up @@ -26,7 +26,7 @@ class CUDNNGRUSequenceTest : public UnsymmetricalComparer<GRUSequenceTest> {
const auto& ops = function->get_ordered_ops();
int seed = 1;
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (std::dynamic_pointer_cast<ov::opset1::Constant>(op)) {
if (op->get_element_type() == ov::element::Type_t::f32) {
ov::Tensor random_tensor(op->get_element_type(), op->get_shape());
ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed++);
Expand Down Expand Up @@ -56,7 +56,7 @@ class LPCNetCUDNNGRUSequenceTest : public UnsymmetricalComparer<GRUSequenceTest>
const auto& ops = function->get_ordered_ops();
int seed = 1;
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (std::dynamic_pointer_cast<ov::opset1::Constant>(op)) {
if (op->get_element_type() == ov::element::Type_t::f32) {
ov::Tensor random_tensor(op->get_element_type(), op->get_shape());
ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed++);
Expand Down Expand Up @@ -118,8 +118,8 @@ class LPCNetCUDNNGRUSequenceTest : public UnsymmetricalComparer<GRUSequenceTest>
true,
direction,
mode);
ov::ResultVector results{std::make_shared<ngraph::opset1::Result>(gru_sequence->output(0)),
std::make_shared<ngraph::opset1::Result>(gru_sequence->output(1))};
ov::ResultVector results{std::make_shared<ov::opset1::Result>(gru_sequence->output(0)),
std::make_shared<ov::opset1::Result>(gru_sequence->output(1))};
function = std::make_shared<ngraph::Function>(results, params, "gru_sequence");
bool ti_found = ngraph::helpers::is_tensor_iterator_exist(function);
EXPECT_EQ(ti_found, false);
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2 changes: 1 addition & 1 deletion ...es/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_cell.cpp
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Expand Up @@ -37,7 +37,7 @@ class CUDNNLSTMCellTest : public LSTMCellTest {
const auto& ops = function->get_ordered_ops();
int seed = SEED_FIRST;
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (std::dynamic_pointer_cast<ov::opset1::Constant>(op)) {
ov::Tensor random_tensor(op->get_element_type(), op->get_shape());
ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, seed);
auto constant = std::make_shared<ov::op::v0::Constant>(random_tensor);
Expand Down
2 changes: 1 addition & 1 deletion ...vidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp
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Expand Up @@ -26,7 +26,7 @@ class CUDALSTMSequenceTest : public UnsymmetricalComparer<LSTMSequenceTest> {
int counter = 1;
const auto& ops = function->get_ordered_ops();
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (std::dynamic_pointer_cast<ov::opset1::Constant>(op)) {
if (op->get_element_type() == ov::element::Type_t::f32) {
ov::Tensor random_tensor(op->get_element_type(), op->get_shape());
ov::test::utils::fill_tensor_random(random_tensor, up_to - start_from, start_from, 1, counter++);
Expand Down
12 changes: 6 additions & 6 deletions modules/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/topk.cpp
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Expand Up @@ -23,14 +23,14 @@ const std::vector<int64_t> k = {
10,
};

const std::vector<ngraph::opset4::TopK::Mode> modes = {
ngraph::opset4::TopK::Mode::MIN,
ngraph::opset4::TopK::Mode::MAX,
const std::vector<ov::opset4::TopK::Mode> modes = {
ov::opset4::TopK::Mode::MIN,
ov::opset4::TopK::Mode::MAX,
};

const std::vector<ngraph::opset4::TopK::SortType> sortTypes = {
ngraph::opset4::TopK::SortType::SORT_INDICES,
ngraph::opset4::TopK::SortType::SORT_VALUES,
const std::vector<ov::opset4::TopK::SortType> sortTypes = {
ov::opset4::TopK::SortType::SORT_INDICES,
ov::opset4::TopK::SortType::SORT_VALUES,
};

const std::vector<int64_t> axes3D = {
Expand Down
6 changes: 3 additions & 3 deletions modules/nvidia_plugin/tests/unit/cuda_multi_graph_test.cpp
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Expand Up @@ -68,7 +68,7 @@ class AddMul {
const auto add1 = ngraph::builder::makeEltwise(params[2], params[3], EltwiseTypes::ADD);

const auto mul = ngraph::builder::makeEltwise(add0, add1, EltwiseTypes::MULTIPLY);
const auto result = std::make_shared<ngraph::opset1::Result>(mul);
const auto result = std::make_shared<ov::opset1::Result>(mul);
return std::make_shared<ov::Model>(result, params, "AddMul");
}

Expand Down Expand Up @@ -114,8 +114,8 @@ class AddConcat {

constexpr int64_t axis = CONCAT_AXIS;
const auto concat =
std::make_shared<ngraph::opset1::Concat>(ov::OutputVector{add0, add1}, axis);
const auto result = std::make_shared<ngraph::opset1::Result>(concat);
std::make_shared<ov::opset1::Concat>(ov::OutputVector{add0, add1}, axis);
const auto result = std::make_shared<ov::opset1::Result>(concat);
return std::make_shared<ov::Model>(result, params, "AddConcat");
}

Expand Down

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