-// Copyright (C) 2020 Intel Corporation
+// Copyright (C) 2019-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
+#include <transformations/op_conversions/convert_batch_to_space.hpp>
+#include <transformations/op_conversions/convert_space_to_batch.hpp>
+
#include "layer_test_utils.hpp"
+#include "plugin_config.hpp"
namespace LayerTestsUtils {
-LayerTestsCommon::LayerTestsCommon() {
- core = PluginCache::get().ie(targetDevice).get();
+LayerTestsCommon::LayerTestsCommon() : threshold(1e-2f) {
+ core = PluginCache::get().ie(targetDevice);
}
void LayerTestsCommon::Run() {
SKIP_IF_CURRENT_TEST_IS_DISABLED()
- ConfigurePlugin();
LoadNetwork();
Infer();
Validate();
}
-LayerTestsCommon::~LayerTestsCommon() {
- if (!configuration.empty() || targetDevice.find(CommonTestUtils::DEVICE_GPU) != std::string::npos) {
- PluginCache::get().reset();
- }
-}
-
InferenceEngine::Blob::Ptr LayerTestsCommon::GenerateInput(const InferenceEngine::InputInfo &info) const {
return FuncTestUtils::createAndFillBlob(info.getTensorDesc());
}
switch (precision) {
case InferenceEngine::Precision::FP32:
Compare(reinterpret_cast<const float *>(expectedBuffer), reinterpret_cast<const float *>(actualBuffer),
- size, 1e-2f);
+ size, threshold);
break;
case InferenceEngine::Precision::I32:
Compare(reinterpret_cast<const std::int32_t *>(expectedBuffer),
}
}
-void LayerTestsCommon::ConfigurePlugin() const {
- if (!configuration.empty()) {
- core->SetConfig(configuration, targetDevice);
+void LayerTestsCommon::Compare(const InferenceEngine::Blob::Ptr &expected, const InferenceEngine::Blob::Ptr &actual) {
+ auto get_raw_buffer = [] (const InferenceEngine::Blob::Ptr &blob) {
+ auto memory = InferenceEngine::as<InferenceEngine::MemoryBlob>(blob);
+ IE_ASSERT(memory);
+ const auto lockedMemory = memory->wmap();
+ return lockedMemory.as<const std::uint8_t *>();
+ };
+ const auto expectedBuffer = get_raw_buffer(expected);
+ const auto actualBuffer = get_raw_buffer(actual);
+
+ const auto &precision = actual->getTensorDesc().getPrecision();
+ const auto &size = actual->size();
+ switch (precision) {
+ case InferenceEngine::Precision::FP32:
+ Compare(reinterpret_cast<const float *>(expectedBuffer), reinterpret_cast<const float *>(actualBuffer),
+ size, threshold);
+ break;
+ case InferenceEngine::Precision::I32:
+ Compare(reinterpret_cast<const std::int32_t *>(expectedBuffer),
+ reinterpret_cast<const std::int32_t *>(actualBuffer), size, 0);
+ break;
+ default:
+ FAIL() << "Comparator for " << precision << " precision isn't supported";
}
}
void LayerTestsCommon::LoadNetwork() {
cnnNetwork = InferenceEngine::CNNNetwork{function};
+ PreparePluginConfiguration(this);
ConfigureNetwork();
- executableNetwork = core->LoadNetwork(cnnNetwork, targetDevice);
+ executableNetwork = core->LoadNetwork(cnnNetwork, targetDevice, configuration);
}
void LayerTestsCommon::Infer() {
inferRequest = executableNetwork.CreateInferRequest();
+ inputs.clear();
- for (const auto &input : cnnNetwork.getInputsInfo()) {
+ for (const auto &input : executableNetwork.GetInputsInfo()) {
const auto &info = input.second;
-
auto blob = GenerateInput(*info);
inferRequest.SetBlob(info->name(), blob);
inputs.push_back(blob);
}
- inferRequest.Infer();
-}
-
-std::vector<InferenceEngine::Blob::Ptr> LayerTestsCommon::GetOutputs() {
- auto outputs = std::vector<InferenceEngine::Blob::Ptr>{};
- for (const auto &output : cnnNetwork.getOutputsInfo()) {
- const auto &name = output.first;
- outputs.push_back(inferRequest.GetBlob(name));
- }
- return outputs;
-}
-
-void LayerTestsCommon::Compare(const std::vector<std::vector<std::uint8_t>>& expectedOutputs, const std::vector<InferenceEngine::Blob::Ptr>& actualOutputs) {
- for (std::size_t outputIndex = 0; outputIndex < expectedOutputs.size(); ++outputIndex) {
- const auto &expected = expectedOutputs[outputIndex];
- const auto &actual = actualOutputs[outputIndex];
- Compare(expected, actual);
+ if (configuration.count(InferenceEngine::PluginConfigParams::KEY_DYN_BATCH_ENABLED) &&
+ configuration.count(InferenceEngine::PluginConfigParams::YES)) {
+ auto batchSize = executableNetwork.GetInputsInfo().begin()->second->getTensorDesc().getDims()[0] / 2;
+ inferRequest.SetBatch(batchSize);
}
+ inferRequest.Infer();
}
-void LayerTestsCommon::Validate() {
+std::vector<std::vector<std::uint8_t>> LayerTestsCommon::CalculateRefs() {
// nGraph interpreter does not support f16
// IE converts f16 to f32
ngraph::pass::ConvertPrecision<ngraph::element::Type_t::f16, ngraph::element::Type_t::f32>().run_on_function(function);
function->validate_nodes_and_infer_types();
auto referenceInputs = std::vector<std::vector<std::uint8_t>>(inputs.size());
for (std::size_t i = 0; i < inputs.size(); ++i) {
- const auto &input = inputs[i];
- const auto &inputSize = input->byteSize();
+ const auto& input = inputs[i];
+ const auto& inputSize = input->byteSize();
- auto &referenceInput = referenceInputs[i];
+ auto& referenceInput = referenceInputs[i];
referenceInput.resize(inputSize);
auto memory = InferenceEngine::as<InferenceEngine::MemoryBlob>(input);
IE_ASSERT(memory);
const auto lockedMemory = memory->wmap();
- const auto buffer = lockedMemory.as<const std::uint8_t *>();
+ const auto buffer = lockedMemory.as<const std::uint8_t*>();
std::copy(buffer, buffer + inputSize, referenceInput.data());
}
- const auto &actualOutputs = GetOutputs();
- const auto &convertType = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(actualOutputs[0]->getTensorDesc().getPrecision());
+ auto ieOutPrc = outPrc;
+ if (outPrc == InferenceEngine::Precision::UNSPECIFIED) {
+ const auto &actualOutputs = GetOutputs();
+ ieOutPrc = actualOutputs[0]->getTensorDesc().getPrecision();
+ }
+
+ const auto &convertType = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(ieOutPrc);
std::vector<std::vector<std::uint8_t>> expectedOutputs;
switch (refMode) {
case INTERPRETER: {
// reference inference on device with other options and nGraph function has to be implemented here
break;
}
+ case INTERPRETER_TRANSFORMATIONS: {
+ auto cloned_function = ngraph::clone_function(*function);
+
+ // todo: add functionality to configure the necessary transformations for each test separately
+ ngraph::pass::Manager m;
+ m.register_pass<ngraph::pass::ConvertSpaceToBatch>();
+ m.register_pass<ngraph::pass::ConvertBatchToSpace>();
+ m.run_passes(cloned_function);
+ expectedOutputs = ngraph::helpers::interpreterFunction(cloned_function, referenceInputs, convertType);
+ break;
+ }
}
+ return expectedOutputs;
+}
+
+std::vector<InferenceEngine::Blob::Ptr> LayerTestsCommon::GetOutputs() {
+ auto outputs = std::vector<InferenceEngine::Blob::Ptr>{};
+ for (const auto &output : executableNetwork.GetOutputsInfo()) {
+ const auto &name = output.first;
+ outputs.push_back(inferRequest.GetBlob(name));
+ }
+ return outputs;
+}
+
+void LayerTestsCommon::Compare(const std::vector<std::vector<std::uint8_t>>& expectedOutputs, const std::vector<InferenceEngine::Blob::Ptr>& actualOutputs) {
+ for (std::size_t outputIndex = 0; outputIndex < expectedOutputs.size(); ++outputIndex) {
+ const auto& expected = expectedOutputs[outputIndex];
+ const auto& actual = actualOutputs[outputIndex];
+ Compare(expected, actual);
+ }
+}
+
+void LayerTestsCommon::Validate() {
+ auto expectedOutputs = CalculateRefs();
+ const auto& actualOutputs = GetOutputs();
+
if (expectedOutputs.empty()) {
return;
}
IE_ASSERT(actualOutputs.size() == expectedOutputs.size())
- << "nGraph interpreter has " << expectedOutputs.size() << " outputs, while IE " << actualOutputs.size();
+ << "nGraph interpreter has " << expectedOutputs.size() << " outputs, while IE " << actualOutputs.size();
Compare(expectedOutputs, actualOutputs);
}
void LayerTestsCommon::SetRefMode(RefMode mode) {
refMode = mode;
}
+
+std::shared_ptr<ngraph::Function> LayerTestsCommon::GetFunction() {
+ return function;
+}
+
+std::map<std::string, std::string>& LayerTestsCommon::GetConfiguration() {
+ return configuration;
+}
} // namespace LayerTestsUtils
projects / platform / upstream / dldt.git / blobdiff