Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Shared onnx tests to API2.0 #21726

Merged
merged 1 commit into from
Dec 19, 2023
Merged

Shared onnx tests to API2.0 #21726

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 4 additions & 4 deletions src/tests/functional/plugin/shared/include/onnx/quantized_models_tests.hpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,19 +5,19 @@
#pragma once

#include <string>
#include "shared_test_classes/base/layer_test_utils.hpp"
#include "shared_test_classes/base/ov_subgraph.hpp"

namespace ONNXTestsDefinitions {

class QuantizedModelsTests : public testing::WithParamInterface<std::string>,
virtual public LayerTestsUtils::LayerTestsCommon {
virtual public ov::test::SubgraphBaseStaticTest {
public:
static std::string getTestCaseName(const testing::TestParamInfo<std::string>& obj);

protected:
void SetUp() override;
using LayerInputTypes = std::unordered_map<std::string, std::vector<ngraph::element::Type_t>>;
void runModel(const char* model, const LayerInputTypes& expected_layer_input_types, float thr);
using LayerInputTypes = std::unordered_map<std::string, std::vector<ov::element::Type>>;
void run_model(const char* model, const LayerInputTypes& expected_layer_input_types, float thr);
};

} // namespace ONNXTestsDefinitions
26 changes: 10 additions & 16 deletions src/tests/functional/plugin/shared/src/onnx/quantized_models_tests.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -24,15 +24,13 @@ static std::string getModelFullPath(const char* path) {
FileUtils::makePath<char>(ov::test::utils::getExecutableDirectory(), TEST_MODELS), path);
}

void QuantizedModelsTests::runModel(const char* model, const LayerInputTypes& expected_layer_input_types, float thr) {
threshold = thr;
auto ie = getCore();
auto network = ie->ReadNetwork(getModelFullPath(model));
function = network.getFunction();
Run();
auto runtime_function = executableNetwork.GetExecGraphInfo().getFunction();
void QuantizedModelsTests::run_model(const char* model, const LayerInputTypes& expected_layer_input_types, float thr) {
abs_threshold = thr;
function = core->read_model(getModelFullPath(model));
ov::test::SubgraphBaseStaticTest::run();
auto runtime_model = compiledModel.get_runtime_model();
int ops_found = 0;
for (const auto& node : runtime_function->get_ordered_ops()) {
for (const auto& node : runtime_model->get_ordered_ops()) {
const auto& name = node->get_friendly_name();
if (expected_layer_input_types.count(name)) {
ops_found++;
Expand All @@ -47,25 +45,21 @@ void QuantizedModelsTests::runModel(const char* model, const LayerInputTypes& ex
}

TEST_P(QuantizedModelsTests, MaxPoolQDQ) {
SKIP_IF_CURRENT_TEST_IS_DISABLED();
runModel("max_pool_qdq.onnx", {{"890_original", {ngraph::element::u8}}}, 1e-5);
run_model("max_pool_qdq.onnx", {{"890_original", {ov::element::u8}}}, 1e-5);
}

TEST_P(QuantizedModelsTests, MaxPoolFQ) {
SKIP_IF_CURRENT_TEST_IS_DISABLED();
runModel("max_pool_fq.onnx", {{"887_original", {ngraph::element::u8}}}, 1e-5);
run_model("max_pool_fq.onnx", {{"887_original", {ov::element::u8}}}, 1e-5);
}

TEST_P(QuantizedModelsTests, ConvolutionQDQ) {
SKIP_IF_CURRENT_TEST_IS_DISABLED();
// activations have type uint8 and weights int8
runModel("convolution_qdq.onnx", {{"908_original", {ngraph::element::u8, ngraph::element::i8}}}, 1.5e-2);
run_model("convolution_qdq.onnx", {{"908_original", {ov::element::u8, ov::element::i8}}}, 1.5e-2);
}

TEST_P(QuantizedModelsTests, ConvolutionFQ) {
SKIP_IF_CURRENT_TEST_IS_DISABLED();
// activations have type uint8 and weights int8
runModel("convolution_fq.onnx", {{"902_original", {ngraph::element::u8, ngraph::element::i8}}}, 1.5e-2);
run_model("convolution_fq.onnx", {{"902_original", {ov::element::u8, ov::element::i8}}}, 1.5e-2);
}

} // namespace ONNXTestsDefinitions
Loading