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Eliminate builder functions
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@olpipi
olpipi committed Aug 10, 2023
1 parent 0193980 commit f4e84fc
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Showing 10 changed files with 60 additions and 59 deletions.
16 changes: 10 additions & 6 deletions .../tests/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data.cpp
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Expand Up @@ -92,12 +92,17 @@ class ConvolutionBackpropDataExtendedLayerTest
bool addBiases = false,
const std::vector<float> &filterWeights = {},
const std::vector<float> &biasesWeights = {}) {
bool randomFilterWeights = filterWeights.empty();
auto shape = in.get_shape();
std::vector<size_t> filterWeightsShape = {shape[1], numOutChannels};
filterWeightsShape.insert(filterWeightsShape.end(), filterSize.begin(), filterSize.end());
auto filterWeightsNode =
ngraph::builder::makeConstant(type, filterWeightsShape, filterWeights, randomFilterWeights);
std::shared_ptr<ov::op::v0::Constant> filterWeightsNode;
if (filterWeights.empty()) {
ov::Tensor random_tensor(type, filterWeightsShape);
ov::test::utils::fill_tensor_random(random_tensor);
auto constant = std::make_shared<ov::op::v0::Constant>(random_tensor);
} else {
filterWeightsNode = std::make_shared<ov::op::v0::Constant>(type, filterWeightsShape, filterWeights);
}

return makeConvolutionBackpropData(in,
filterWeightsNode,
Expand Down Expand Up @@ -149,10 +154,9 @@ class ConvolutionBackpropDataExtendedLayerTest
std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType, outputPad) =
convBackpropDataParams;
auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision);
ov::ParameterVector params {std::make_shared<ov::op::v0::Parameter>(ngPrc, ov::Shape(inputShape)))};
ov::ParameterVector params {std::make_shared<ov::op::v0::Parameter>(ngPrc, ov::Shape(inputShape))};

auto outputShapeNode =
ngraph::builder::makeConstant(ov::element::Type_t::i64, {outputShapeData.size()}, outputShapeData);
auto outputShapeNode = std::make_shared<ov::op::v0::Constant>(ov::element::Type_t::i64, ov::Shape{outputShapeData.size()}, outputShapeData);
auto paramOuts =
ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ov::op::v0::Parameter>(params));
auto convBackpropData = std::dynamic_pointer_cast<ngraph::opset1::ConvolutionBackpropData>(
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22 changes: 15 additions & 7 deletions ...ts/functional/shared_tests_instances/single_layer_tests/convolution_backprop_data_add.cpp
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Expand Up @@ -94,9 +94,15 @@ class ConvolutionBackpropDataAddExtendedLayerTest
auto shape = in.get_shape();
std::vector<size_t> filterWeightsShape = {shape[1], numOutChannels};
filterWeightsShape.insert(filterWeightsShape.end(), filterSize.begin(), filterSize.end());
auto filterWeightsNode =
ngraph::builder::makeConstant(type, filterWeightsShape, filterWeights, randomFilterWeights);

std::shared_ptr<ov::Node> filterWeightsNode;
if (filterWeights.empty()) {
ov::Tensor random_tensor(type, filterWeightsShape);
ov::test::utils::fill_tensor_random(random_tensor);
filterWeightsNode = std::make_shared<ov::op::v0::Constant>(random_tensor);
} else {
filterWeightsNode = std::make_shared<ov::op::v0::Constant>(type, filterWeightsShape, filterWeights);
}
return makeConvolutionBackpropData(in,
filterWeightsNode,
output,
Expand Down Expand Up @@ -147,10 +153,9 @@ class ConvolutionBackpropDataAddExtendedLayerTest
std::tie(kernel, stride, padBegin, padEnd, dilation, convOutChannels, padType, outputPad) =
convBackpropDataParams;
auto ngPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision);
ov::ParameterVector params {std::make_shared<ov::op::v0::Parameter>(ngPrc, ov::Shape(inputShape)))};
ov::ParameterVector params {std::make_shared<ov::op::v0::Parameter>(ngPrc, ov::Shape(inputShape))};

auto outputShapeNode =
ngraph::builder::makeConstant(ov::element::Type_t::i64, {outputShapeData.size()}, outputShapeData);
auto outputShapeNode = std::make_shared<ov::op::v0::Constant>(ov::element::Type_t::i64, ov::Shape{outputShapeData.size()}, outputShapeData);
auto paramOuts =
ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ov::op::v0::Parameter>(params));
auto convBackpropData = std::dynamic_pointer_cast<ngraph::opset1::ConvolutionBackpropData>(
Expand All @@ -164,8 +169,11 @@ class ConvolutionBackpropDataAddExtendedLayerTest
dilation,
padType,
convOutChannels));
auto addConstant = ngraph::builder::makeConstant(ngPrc, outputShapeData, outputShapeData, true);
auto add = ngraph::builder::makeEltwise(convBackpropData, addConstant, ngraph::helpers::EltwiseTypes::ADD);

ov::Tensor random_tensor(ngPrc, outputShapeData);
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)};
function = std::make_shared<ngraph::Function>(results, params, "convolutionBackpropData");
}
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4 changes: 2 additions & 2 deletions ...s/functional/shared_tests_instances/single_layer_tests/convolution_biasadd_activation.hpp
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Expand Up @@ -122,13 +122,13 @@ class BasicConvolutionBiasAddActivationLayerTest
}
auto biasLayer = std::make_shared<ov::op::v0::Constant>(ngNetPrc, biasShape);

auto biasAddLayer = ngraph::builder::makeEltwise(convLayer, biasLayer, ngraph::helpers::EltwiseTypes::ADD);
auto biasAddLayer = std::make_shared<ov::op::v1::Add>(convLayer, biasLayer);

std::shared_ptr<ov::Node> lastNode;
if constexpr (HasAddNode) {
auto addParam = std::make_shared<ngraph::opset1::Parameter>(ngNetPrc, convLayer->get_output_shape(0));
params.push_back(addParam);
auto addLayer = ngraph::builder::makeEltwise(biasAddLayer, addParam, ngraph::helpers::EltwiseTypes::ADD);
auto addLayer = std::make_shared<ov::op::v1::Add>(biasAddLayer, addParam);
lastNode = addLayer;
} else {
lastNode = biasAddLayer;
Expand Down
8 changes: 5 additions & 3 deletions ...nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/cuda_eltwise.cpp
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Expand Up @@ -247,15 +247,17 @@ void CudaEltwiseLayerTest::SetUp() {
[](const auto& value) { return static_cast<int>(static_cast<float>(value)) == 0; },
1);
}
secondaryInput = ngraph::builder::makeConstant(netType, shape, data);
secondaryInput = std::make_shared<ov::op::v0::Constant>(netType, shape, data);
break;
}
case ngraph::helpers::EltwiseTypes::POWER: {
secondaryInput = ngraph::builder::makeConstant<float>(netType, shape, {}, is_random, 3);
ov::Tensor random_tensor(netType, shape);
ov::test::utils::fill_tensor_random(random_tensor, 3, -3);
secondaryInput = std::make_shared<ov::op::v0::Constant>(random_tensor);
break;
}
default: {
secondaryInput = ngraph::builder::makeConstant<float>(netType, shape, data);
secondaryInput = std::make_shared<ov::op::v0::Constant>(netType, shape, data);
}
}
}
Expand Down
31 changes: 12 additions & 19 deletions ...dia_plugin/tests/functional/shared_tests_instances/single_layer_tests/fully_connected.cpp
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Expand Up @@ -3,7 +3,6 @@
//

#include <cuda_test_constants.hpp>
#include <ngraph_functions/builders.hpp>
#include <vector>

#include "finite_comparer.hpp"
Expand Down Expand Up @@ -95,10 +94,8 @@ class FullyConnectedLayerTest : public testing::WithParamInterface<FullyConnecte
auto thirdInput = std::make_shared<ov::op::v0::Constant>(ngPrc, shapeRelatedParams.input3);
auto paramOuts =
ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ov::op::v0::Parameter>(params));
auto MatMul = std::dynamic_pointer_cast<ov::op::v0::MatMul>(ngraph::builder::makeMatMul(
paramOuts[0], secondaryInput, shapeRelatedParams.input1.second, shapeRelatedParams.input2.second));
auto Add = std::dynamic_pointer_cast<ov::op::v1::Add>(
ngraph::builder::makeEltwise(MatMul, thirdInput, ngraph::helpers::EltwiseTypes::ADD));
auto MatMul = std::make_shared<ov::op::v0::MatMul>(paramOuts[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)};
function = std::make_shared<ngraph::Function>(results, params, "FullyConnected");
}
Expand Down Expand Up @@ -210,20 +207,16 @@ class FullyConnectedLayer2MatMulTest : public testing::WithParamInterface<FullyC
matmul1SecondaryInput = std::make_shared<ov::op::v0::Constant>(ngPrc, shapeRelatedParams.matmul1_input2.first);
}

auto paramOuts =
ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ov::op::v0::Parameter>(params));
auto matMul0 = std::dynamic_pointer_cast<ov::op::v0::MatMul>(
ngraph::builder::makeMatMul(paramOuts[0],
matmul0SecondaryInput,
shapeRelatedParams.matmul1_input1.second,
shapeRelatedParams.matmul1_input2.second));
auto matMul1 = std::dynamic_pointer_cast<ov::op::v0::MatMul>(
ngraph::builder::makeMatMul(paramOuts[1],
matmul1SecondaryInput,
shapeRelatedParams.matmul2_input1.second,
shapeRelatedParams.matmul2_input2.second));
auto Add = std::dynamic_pointer_cast<ov::op::v1::Add>(
ngraph::builder::makeEltwise(matMul0, matMul1, ngraph::helpers::EltwiseTypes::ADD));
auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ov::op::v0::Parameter>(params));
auto matMul0 = std::make_shared<ov::op::v0::MatMul>(paramOuts[0],
matmul0SecondaryInput,
shapeRelatedParams.matmul1_input1.second,
shapeRelatedParams.matmul1_input2.second);
auto matMul1 = std::make_shared<ov::op::v0::MatMul>(paramOuts[1],
matmul1SecondaryInput,
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)};
function = std::make_shared<ngraph::Function>(results, params, "FullyConnected");
}
Expand Down
7 changes: 3 additions & 4 deletions ...les/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_cell.cpp
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Expand Up @@ -34,10 +34,9 @@ class CUDNNGRUCellTest : public UnsymmetricalComparer<GRUCellTest> {
int seed = SEED_FIRST;
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
const auto constant = ngraph::builder::makeConstant(
op->get_element_type(), op->get_shape(), std::vector<float>{}, true, up_to, start_from, seed);
function->replace_node(op, constant);
++seed;
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));
}
}

Expand Down
12 changes: 6 additions & 6 deletions ...nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/gru_sequence.cpp
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Expand Up @@ -27,9 +27,9 @@ class CUDNNGRUSequenceTest : public UnsymmetricalComparer<GRUSequenceTest> {
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (op->get_element_type() == ov::element::Type_t::f32) {
const auto constant = ngraph::builder::makeConstant(
op->get_element_type(), op->get_shape(), std::vector<float>{}, true, up_to, start_from, seed++);
function->replace_node(op, constant);
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));
}
}
}
Expand Down Expand Up @@ -57,9 +57,9 @@ class LPCNetCUDNNGRUSequenceTest : public UnsymmetricalComparer<GRUSequenceTest>
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (op->get_element_type() == ov::element::Type_t::f32) {
const auto constant = ngraph::builder::makeConstant(
op->get_element_type(), op->get_shape(), std::vector<float>{}, true, up_to, start_from, seed++);
function->replace_node(op, constant);
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));
}
}
}
Expand Down
5 changes: 3 additions & 2 deletions ...es/nvidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_cell.cpp
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Expand Up @@ -37,8 +37,9 @@ class CUDNNLSTMCellTest : public LSTMCellTest {
int seed = SEED_FIRST;
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
const auto constant = ngraph::builder::makeConstant(
op->get_element_type(), op->get_shape(), std::vector<float>{}, true, up_to, start_from, seed);
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);
function->replace_node(op, constant);
++seed;
}
Expand Down
11 changes: 3 additions & 8 deletions ...vidia_plugin/tests/functional/shared_tests_instances/single_layer_tests/lstm_sequence.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -26,14 +26,9 @@ class CUDALSTMSequenceTest : public UnsymmetricalComparer<LSTMSequenceTest> {
for (const auto& op : ops) {
if (std::dynamic_pointer_cast<ngraph::opset1::Constant>(op)) {
if (op->get_element_type() == ov::element::Type_t::f32) {
const auto constant = ngraph::builder::makeConstant(op->get_element_type(),
op->get_shape(),
std::vector<float>{},
true,
up_to,
start_from,
counter++);
function->replace_node(op, constant);
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));
}
}
}
Expand Down
3 changes: 1 addition & 2 deletions modules/nvidia_plugin/tests/unit/test_networks.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -18,8 +18,7 @@ inline std::shared_ptr<ngraph::Function> CreateMatMulTestNetwork() {
auto secondaryInput = std::make_shared<ov::op::v0::Constant>(ngPrc, ov::Shape{3, 2, 10, 20});
auto paramOuts =
ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ov::op::v0::Parameter>(params));
auto MatMul = std::dynamic_pointer_cast<ov::op::v0::MatMul>(
ngraph::builder::makeMatMul(paramOuts[0], secondaryInput, false, false));
auto MatMul = std::make_shared<ov::op::v0::MatMul>(paramOuts[0], secondaryInput, false, false);
ov::ResultVector results{std::make_shared<ngraph::opset1::Result>(MatMul)};
return std::make_shared<ngraph::Function>(results, params, "MatMul");
}
Expand Down

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