--- /dev/null
+/*
+ * Copyright (C) 2017 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#define LOG_TAG "neuralnetworks_hidl_hal_test"
+
+#include "VtsHalNeuralnetworksV1_0TargetTest.h"
+#include <android-base/logging.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <hidlmemory/mapping.h>
+#include <string>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace V1_0 {
+namespace vts {
+namespace functional {
+
+// A class for test environment setup
+NeuralnetworksHidlEnvironment::NeuralnetworksHidlEnvironment() {}
+
+NeuralnetworksHidlEnvironment* NeuralnetworksHidlEnvironment::getInstance() {
+ // This has to return a "new" object because it is freed inside
+ // ::testing::AddGlobalTestEnvironment when the gtest is being torn down
+ static NeuralnetworksHidlEnvironment* instance = new NeuralnetworksHidlEnvironment();
+ return instance;
+}
+
+void NeuralnetworksHidlEnvironment::registerTestServices() {
+ registerTestService("android.hardware.neuralnetworks", "1.0", "IDevice");
+}
+
+// The main test class for NEURALNETWORK HIDL HAL.
+void NeuralnetworksHidlTest::SetUp() {
+ std::string instance =
+ NeuralnetworksHidlEnvironment::getInstance()->getServiceName(IDevice::descriptor);
+ LOG(INFO) << "running vts test with instance: " << instance;
+ device = ::testing::VtsHalHidlTargetTestBase::getService<IDevice>(instance);
+ ASSERT_NE(nullptr, device.get());
+}
+
+void NeuralnetworksHidlTest::TearDown() {}
+
+// create device test
+TEST_F(NeuralnetworksHidlTest, CreateDevice) {}
+
+// status test
+TEST_F(NeuralnetworksHidlTest, StatusTest) {
+ DeviceStatus status = device->getStatus();
+ EXPECT_EQ(DeviceStatus::AVAILABLE, status);
+}
+
+// initialization
+TEST_F(NeuralnetworksHidlTest, InitializeTest) {
+ Return<void> ret = device->initialize([](const Capabilities& capabilities) {
+ EXPECT_NE(nullptr, capabilities.supportedOperationTypes.data());
+ EXPECT_NE(0ull, capabilities.supportedOperationTypes.size());
+ EXPECT_EQ(0u, static_cast<uint32_t>(capabilities.cachesCompilation) & ~0x1);
+ EXPECT_LT(0.0f, capabilities.bootupTime);
+ EXPECT_LT(0.0f, capabilities.float16Performance.execTime);
+ EXPECT_LT(0.0f, capabilities.float16Performance.powerUsage);
+ EXPECT_LT(0.0f, capabilities.float32Performance.execTime);
+ EXPECT_LT(0.0f, capabilities.float32Performance.powerUsage);
+ EXPECT_LT(0.0f, capabilities.quantized8Performance.execTime);
+ EXPECT_LT(0.0f, capabilities.quantized8Performance.powerUsage);
+ });
+ EXPECT_TRUE(ret.isOk());
+}
+
+namespace {
+// create the model
+Model createTestModel() {
+ const std::vector<float> operand2Data = {5.0f, 6.0f, 7.0f, 8.0f};
+ const uint32_t size = operand2Data.size() * sizeof(float);
+
+ const uint32_t operand1 = 0;
+ const uint32_t operand2 = 1;
+ const uint32_t operand3 = 2;
+
+ const std::vector<Operand> operands = {
+ {
+ .type = OperandType::FLOAT32,
+ .dimensions = {1, 2, 2, 1},
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .location = {.poolIndex = static_cast<uint32_t>(LocationValues::LOCATION_AT_RUN_TIME),
+ .offset = 0,
+ .length = 0},
+ },
+ {
+ .type = OperandType::FLOAT32,
+ .dimensions = {1, 2, 2, 1},
+ .numberOfConsumers = 1,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .location = {.poolIndex = static_cast<uint32_t>(LocationValues::LOCATION_SAME_BLOCK),
+ .offset = 0,
+ .length = size},
+ },
+ {
+ .type = OperandType::FLOAT32,
+ .dimensions = {1, 2, 2, 1},
+ .numberOfConsumers = 0,
+ .scale = 0.0f,
+ .zeroPoint = 0,
+ .location = {.poolIndex = static_cast<uint32_t>(LocationValues::LOCATION_AT_RUN_TIME),
+ .offset = 0,
+ .length = 0},
+ },
+ };
+
+ const std::vector<Operation> operations = {{
+ .type = OperationType::ADD_FLOAT32, .inputs = {operand1, operand2}, .outputs = {operand3},
+ }};
+
+ const std::vector<uint32_t> inputIndexes = {operand1};
+ const std::vector<uint32_t> outputIndexes = {operand3};
+ const std::vector<uint8_t> operandValues(reinterpret_cast<const uint8_t*>(operand2Data.data()),
+ reinterpret_cast<const uint8_t*>(operand2Data.data()) +
+ operand2Data.size() * sizeof(float));
+ const std::vector<hidl_memory> pools = {};
+
+ return {
+ .operands = operands,
+ .operations = operations,
+ .inputIndexes = inputIndexes,
+ .outputIndexes = outputIndexes,
+ .operandValues = operandValues,
+ .pools = pools,
+ };
+}
+
+// allocator helper
+hidl_memory allocateSharedMemory(int64_t size, const std::string& type = "ashmem") {
+ hidl_memory memory;
+
+ sp<IAllocator> allocator = IAllocator::getService(type);
+ if (!allocator.get()) {
+ return {};
+ }
+
+ Return<void> ret = allocator->allocate(size, [&](bool success, const hidl_memory& mem) {
+ ASSERT_TRUE(success);
+ memory = mem;
+ });
+ if (!ret.isOk()) {
+ return {};
+ }
+
+ return memory;
+}
+} // anonymous namespace
+
+// supported subgraph test
+TEST_F(NeuralnetworksHidlTest, SupportedSubgraphTest) {
+ Model model = createTestModel();
+ std::vector<bool> supported;
+ Return<void> ret = device->getSupportedSubgraph(
+ model, [&](const hidl_vec<bool>& hidl_supported) { supported = hidl_supported; });
+ ASSERT_TRUE(ret.isOk());
+ EXPECT_EQ(/*model.operations.size()*/ 0ull, supported.size());
+}
+
+// execute simple graph
+TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphTest) {
+ std::vector<float> inputData = {1.0f, 2.0f, 3.0f, 4.0f};
+ std::vector<float> outputData = {-1.0f, -1.0f, -1.0f, -1.0f};
+ std::vector<float> expectedData = {6.0f, 8.0f, 10.0f, 12.0f};
+ const uint32_t INPUT = 0;
+ const uint32_t OUTPUT = 1;
+
+ // prpeare request
+ Model model = createTestModel();
+ sp<IPreparedModel> preparedModel = device->prepareModel(model);
+ ASSERT_NE(nullptr, preparedModel.get());
+
+ // prepare inputs
+ uint32_t inputSize = static_cast<uint32_t>(inputData.size() * sizeof(float));
+ uint32_t outputSize = static_cast<uint32_t>(outputData.size() * sizeof(float));
+ std::vector<InputOutputInfo> inputs = {{
+ .location = {.poolIndex = INPUT, .offset = 0, .length = inputSize}, .dimensions = {},
+ }};
+ std::vector<InputOutputInfo> outputs = {{
+ .location = {.poolIndex = OUTPUT, .offset = 0, .length = outputSize}, .dimensions = {},
+ }};
+ std::vector<hidl_memory> pools = {allocateSharedMemory(inputSize),
+ allocateSharedMemory(outputSize)};
+ ASSERT_NE(0ull, pools[INPUT].size());
+ ASSERT_NE(0ull, pools[OUTPUT].size());
+
+ // load data
+ sp<IMemory> inputMemory = mapMemory(pools[INPUT]);
+ sp<IMemory> outputMemory = mapMemory(pools[OUTPUT]);
+ ASSERT_NE(nullptr, inputMemory.get());
+ ASSERT_NE(nullptr, outputMemory.get());
+ float* inputPtr = reinterpret_cast<float*>(static_cast<void*>(inputMemory->getPointer()));
+ float* outputPtr = reinterpret_cast<float*>(static_cast<void*>(outputMemory->getPointer()));
+ ASSERT_NE(nullptr, inputPtr);
+ ASSERT_NE(nullptr, outputPtr);
+ std::copy(inputData.begin(), inputData.end(), inputPtr);
+ std::copy(outputData.begin(), outputData.end(), outputPtr);
+ inputMemory->commit();
+ outputMemory->commit();
+
+ // execute request
+ bool success = preparedModel->execute({.inputs = inputs, .outputs = outputs, .pools = pools});
+ EXPECT_TRUE(success);
+
+ // validate results { 1+5, 2+6, 3+7, 4+8 }
+ outputMemory->update();
+ std::copy(outputPtr, outputPtr + outputData.size(), outputData.begin());
+ EXPECT_EQ(expectedData, outputData);
+}
+
+} // namespace functional
+} // namespace vts
+} // namespace V1_0
+} // namespace neuralnetworks
+} // namespace hardware
+} // namespace android
+
+using android::hardware::neuralnetworks::V1_0::vts::functional::NeuralnetworksHidlEnvironment;
+
+int main(int argc, char** argv) {
+ ::testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
+ ::testing::InitGoogleTest(&argc, argv);
+ NeuralnetworksHidlEnvironment::getInstance()->init(&argc, argv);
+
+ int status = RUN_ALL_TESTS();
+ return status;
+}
--- /dev/null
+/*
+ * Copyright (C) 2017 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef VTS_HAL_NEURALNETWORKS_V1_0_TARGET_TESTS_H
+#define VTS_HAL_NEURALNETWORKS_V1_0_TARGET_TESTS_H
+
+#include <android/hardware/neuralnetworks/1.0/IDevice.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hidl/allocator/1.0/IAllocator.h>
+
+#include <VtsHalHidlTargetTestBase.h>
+#include <VtsHalHidlTargetTestEnvBase.h>
+#include <gtest/gtest.h>
+#include <string>
+
+using ::android::hardware::neuralnetworks::V1_0::IDevice;
+using ::android::hardware::neuralnetworks::V1_0::IPreparedModel;
+using ::android::hardware::neuralnetworks::V1_0::Capabilities;
+using ::android::hardware::neuralnetworks::V1_0::DeviceStatus;
+using ::android::hardware::neuralnetworks::V1_0::Model;
+using ::android::hardware::neuralnetworks::V1_0::OperationType;
+using ::android::hardware::neuralnetworks::V1_0::PerformanceInfo;
+using ::android::hardware::Return;
+using ::android::hardware::Void;
+using ::android::hardware::hidl_memory;
+using ::android::hardware::hidl_string;
+using ::android::hardware::hidl_vec;
+using ::android::hidl::allocator::V1_0::IAllocator;
+using ::android::hidl::memory::V1_0::IMemory;
+using ::android::sp;
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace V1_0 {
+namespace vts {
+namespace functional {
+
+// A class for test environment setup
+class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvBase {
+ NeuralnetworksHidlEnvironment();
+ NeuralnetworksHidlEnvironment(const NeuralnetworksHidlEnvironment&) = delete;
+ NeuralnetworksHidlEnvironment(NeuralnetworksHidlEnvironment&&) = delete;
+ NeuralnetworksHidlEnvironment& operator=(const NeuralnetworksHidlEnvironment&) = delete;
+ NeuralnetworksHidlEnvironment& operator=(NeuralnetworksHidlEnvironment&&) = delete;
+
+ public:
+ static NeuralnetworksHidlEnvironment* getInstance();
+ virtual void registerTestServices() override;
+};
+
+// The main test class for NEURALNETWORKS HIDL HAL.
+class NeuralnetworksHidlTest : public ::testing::VtsHalHidlTargetTestBase {
+ public:
+ virtual void SetUp() override;
+ virtual void TearDown() override;
+
+ sp<IDevice> device;
+};
+
+} // namespace functional
+} // namespace vts
+} // namespace V1_0
+} // namespace neuralnetworks
+} // namespace hardware
+} // namespace android
+
+#endif // VTS_HAL_NEURALNETWORKS_V1_0_TARGET_TESTS_H
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