Loading neuralnetworks/1.0/IDevice.hal +2 −1 Original line number Diff line number Diff line Loading @@ -18,6 +18,7 @@ package android.hardware.neuralnetworks@1.0; import IEvent; import IPreparedModel; interface IDevice { Loading @@ -25,7 +26,7 @@ interface IDevice { getSupportedSubgraph(Model model) generates(vec<bool> supported); prepareModel(Model model) generates(IPreparedModel preparedModel); prepareModel(Model model, IEvent event) generates(IPreparedModel preparedModel); getStatus() generates(DeviceStatus status); }; neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.cpp +11 −7 Original line number Diff line number Diff line Loading @@ -209,10 +209,14 @@ TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphTest) { const uint32_t INPUT = 0; const uint32_t OUTPUT = 1; // prpeare request // prepare request Model model = createTestModel(); sp<IPreparedModel> preparedModel = device->prepareModel(model); sp<Event> preparationEvent = new Event(); ASSERT_NE(nullptr, preparationEvent.get()); sp<IPreparedModel> preparedModel = device->prepareModel(model, preparationEvent); ASSERT_NE(nullptr, preparedModel.get()); Event::Status preparationStatus = preparationEvent->wait(); EXPECT_EQ(Event::Status::SUCCESS, preparationStatus); // prepare inputs uint32_t inputSize = static_cast<uint32_t>(inputData.size() * sizeof(float)); Loading Loading @@ -245,13 +249,13 @@ TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphTest) { outputMemory->commit(); // execute request sp<Event> event = sp<Event>(new Event()); ASSERT_NE(nullptr, event.get()); sp<Event> executionEvent = new Event(); ASSERT_NE(nullptr, executionEvent.get()); bool success = preparedModel->execute({.inputs = inputs, .outputs = outputs, .pools = pools}, event); executionEvent); EXPECT_TRUE(success); Event::Status status = event->wait(); EXPECT_EQ(Event::Status::SUCCESS, status); Event::Status executionStatus = executionEvent->wait(); EXPECT_EQ(Event::Status::SUCCESS, executionStatus); // validate results { 1+5, 2+6, 3+7, 4+8 } outputMemory->read(); Loading Loading
neuralnetworks/1.0/IDevice.hal +2 −1 Original line number Diff line number Diff line Loading @@ -18,6 +18,7 @@ package android.hardware.neuralnetworks@1.0; import IEvent; import IPreparedModel; interface IDevice { Loading @@ -25,7 +26,7 @@ interface IDevice { getSupportedSubgraph(Model model) generates(vec<bool> supported); prepareModel(Model model) generates(IPreparedModel preparedModel); prepareModel(Model model, IEvent event) generates(IPreparedModel preparedModel); getStatus() generates(DeviceStatus status); };
neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.cpp +11 −7 Original line number Diff line number Diff line Loading @@ -209,10 +209,14 @@ TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphTest) { const uint32_t INPUT = 0; const uint32_t OUTPUT = 1; // prpeare request // prepare request Model model = createTestModel(); sp<IPreparedModel> preparedModel = device->prepareModel(model); sp<Event> preparationEvent = new Event(); ASSERT_NE(nullptr, preparationEvent.get()); sp<IPreparedModel> preparedModel = device->prepareModel(model, preparationEvent); ASSERT_NE(nullptr, preparedModel.get()); Event::Status preparationStatus = preparationEvent->wait(); EXPECT_EQ(Event::Status::SUCCESS, preparationStatus); // prepare inputs uint32_t inputSize = static_cast<uint32_t>(inputData.size() * sizeof(float)); Loading Loading @@ -245,13 +249,13 @@ TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphTest) { outputMemory->commit(); // execute request sp<Event> event = sp<Event>(new Event()); ASSERT_NE(nullptr, event.get()); sp<Event> executionEvent = new Event(); ASSERT_NE(nullptr, executionEvent.get()); bool success = preparedModel->execute({.inputs = inputs, .outputs = outputs, .pools = pools}, event); executionEvent); EXPECT_TRUE(success); Event::Status status = event->wait(); EXPECT_EQ(Event::Status::SUCCESS, status); Event::Status executionStatus = executionEvent->wait(); EXPECT_EQ(Event::Status::SUCCESS, executionStatus); // validate results { 1+5, 2+6, 3+7, 4+8 } outputMemory->read(); Loading