1 /*
2  * Copyright (C) 2021 The Android Open Source Project
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  *      http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 
17 #define LOG_TAG "neuralnetworks_aidl_hal_test"
18 #include "VtsHalNeuralnetworks.h"
19 
20 #include <android-base/logging.h>
21 #include <android/binder_auto_utils.h>
22 #include <android/binder_interface_utils.h>
23 #include <android/binder_manager.h>
24 #include <android/binder_status.h>
25 #include <gtest/gtest.h>
26 #include <memory>
27 #include <string>
28 #include <utility>
29 
30 #include <TestHarness.h>
31 #include <aidl/Vintf.h>
32 #include <nnapi/hal/aidl/Conversions.h>
33 
34 #include "Callbacks.h"
35 #include "GeneratedTestHarness.h"
36 #include "Utils.h"
37 
38 namespace aidl::android::hardware::neuralnetworks::vts::functional {
39 
40 using implementation::PreparedModelCallback;
41 
42 // internal helper function
createPreparedModel(const std::shared_ptr<IDevice> & device,const Model & model,std::shared_ptr<IPreparedModel> * preparedModel,bool reportSkipping)43 void createPreparedModel(const std::shared_ptr<IDevice>& device, const Model& model,
44                          std::shared_ptr<IPreparedModel>* preparedModel, bool reportSkipping) {
45     ASSERT_NE(nullptr, preparedModel);
46     *preparedModel = nullptr;
47 
48     // see if service can handle model
49     std::vector<bool> supportedOperations;
50     const auto supportedCallStatus = device->getSupportedOperations(model, &supportedOperations);
51     ASSERT_TRUE(supportedCallStatus.isOk());
52     ASSERT_NE(0ul, supportedOperations.size());
53     const bool fullySupportsModel = std::all_of(
54             supportedOperations.begin(), supportedOperations.end(), [](bool v) { return v; });
55 
56     // launch prepare model
57     const std::shared_ptr<PreparedModelCallback> preparedModelCallback =
58             ndk::SharedRefBase::make<PreparedModelCallback>();
59     const auto prepareLaunchStatus =
60             device->prepareModel(model, ExecutionPreference::FAST_SINGLE_ANSWER, kDefaultPriority,
61                                  kNoDeadline, {}, {}, kEmptyCacheToken, preparedModelCallback);
62     ASSERT_TRUE(prepareLaunchStatus.isOk()) << prepareLaunchStatus.getDescription();
63 
64     // retrieve prepared model
65     preparedModelCallback->wait();
66     const ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
67     *preparedModel = preparedModelCallback->getPreparedModel();
68 
69     // The getSupportedOperations call returns a list of operations that are guaranteed not to fail
70     // if prepareModel is called, and 'fullySupportsModel' is true i.f.f. the entire model is
71     // guaranteed. If a driver has any doubt that it can prepare an operation, it must return false.
72     // So here, if a driver isn't sure if it can support an operation, but reports that it
73     // successfully prepared the model, the test can continue.
74     if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
75         ASSERT_EQ(nullptr, preparedModel->get());
76         if (!reportSkipping) {
77             return;
78         }
79         LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot prepare "
80                      "model that it does not support.";
81         std::cout << "[          ]   Early termination of test because vendor service cannot "
82                      "prepare model that it does not support."
83                   << std::endl;
84         GTEST_SKIP();
85     }
86 
87     ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
88     ASSERT_NE(nullptr, preparedModel->get());
89 }
90 
SetUp()91 void NeuralNetworksAidlTest::SetUp() {
92     testing::TestWithParam<NeuralNetworksAidlTestParam>::SetUp();
93     ASSERT_NE(kDevice, nullptr);
94     const bool deviceIsResponsive =
95             ndk::ScopedAStatus::fromStatus(AIBinder_ping(kDevice->asBinder().get())).isOk();
96     ASSERT_TRUE(deviceIsResponsive);
97 }
98 
makeNamedDevice(const std::string & name)99 static NamedDevice makeNamedDevice(const std::string& name) {
100     ndk::SpAIBinder binder(AServiceManager_waitForService(name.c_str()));
101     return {name, IDevice::fromBinder(binder)};
102 }
103 
getNamedDevicesImpl()104 static std::vector<NamedDevice> getNamedDevicesImpl() {
105     // Retrieves the name of all service instances that implement IDevice,
106     // including any Lazy HAL instances.
107     const std::vector<std::string> names = ::android::getAidlHalInstanceNames(IDevice::descriptor);
108 
109     // Get a handle to each device and pair it with its name.
110     std::vector<NamedDevice> namedDevices;
111     namedDevices.reserve(names.size());
112     std::transform(names.begin(), names.end(), std::back_inserter(namedDevices), makeNamedDevice);
113     return namedDevices;
114 }
115 
getNamedDevices()116 const std::vector<NamedDevice>& getNamedDevices() {
117     const static std::vector<NamedDevice> devices = getNamedDevicesImpl();
118     return devices;
119 }
120 
printNeuralNetworksAidlTest(const testing::TestParamInfo<NeuralNetworksAidlTestParam> & info)121 std::string printNeuralNetworksAidlTest(
122         const testing::TestParamInfo<NeuralNetworksAidlTestParam>& info) {
123     return gtestCompliantName(getName(info.param));
124 }
125 
126 INSTANTIATE_DEVICE_TEST(NeuralNetworksAidlTest);
127 
128 // Forward declaration from ValidateModel.cpp
129 void validateModel(const std::shared_ptr<IDevice>& device, const Model& model);
130 // Forward declaration from ValidateRequest.cpp
131 void validateRequest(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request);
132 // Forward declaration from ValidateRequest.cpp
133 void validateBurst(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request);
134 // Forward declaration from ValidateRequest.cpp
135 void validateRequestFailure(const std::shared_ptr<IPreparedModel>& preparedModel,
136                             const Request& request);
137 
validateEverything(const std::shared_ptr<IDevice> & device,const Model & model,const Request & request)138 void validateEverything(const std::shared_ptr<IDevice>& device, const Model& model,
139                         const Request& request) {
140     validateModel(device, model);
141 
142     // Create IPreparedModel.
143     std::shared_ptr<IPreparedModel> preparedModel;
144     createPreparedModel(device, model, &preparedModel);
145     if (preparedModel == nullptr) return;
146 
147     validateRequest(preparedModel, request);
148     validateBurst(preparedModel, request);
149     // HIDL also had test that expected executeFenced to fail on received null fd (-1). This is not
150     // allowed in AIDL and will result in EX_TRANSACTION_FAILED.
151 }
152 
validateFailure(const std::shared_ptr<IDevice> & device,const Model & model,const Request & request)153 void validateFailure(const std::shared_ptr<IDevice>& device, const Model& model,
154                      const Request& request) {
155     // TODO: Should this always succeed?
156     //       What if the invalid input is part of the model (i.e., a parameter).
157     validateModel(device, model);
158 
159     // Create IPreparedModel.
160     std::shared_ptr<IPreparedModel> preparedModel;
161     createPreparedModel(device, model, &preparedModel);
162     if (preparedModel == nullptr) return;
163 
164     validateRequestFailure(preparedModel, request);
165 }
166 
TEST_P(ValidationTest,Test)167 TEST_P(ValidationTest, Test) {
168     const Model model = createModel(kTestModel);
169     ExecutionContext context;
170     const Request request = context.createRequest(kTestModel);
171     if (kTestModel.expectFailure) {
172         validateFailure(kDevice, model, request);
173     } else {
174         validateEverything(kDevice, model, request);
175     }
176 }
177 
__anon0ec80da00202(const std::string& testName) 178 INSTANTIATE_GENERATED_TEST(ValidationTest, [](const std::string& testName) {
179     // Skip validation for the "inputs_as_internal" and "all_tensors_as_inputs"
180     // generated tests.
181     return testName.find("inputs_as_internal") == std::string::npos &&
182            testName.find("all_tensors_as_inputs") == std::string::npos;
183 });
184 
toString(Executor executor)185 std::string toString(Executor executor) {
186     switch (executor) {
187         case Executor::SYNC:
188             return "SYNC";
189         case Executor::BURST:
190             return "BURST";
191         case Executor::FENCED:
192             return "FENCED";
193         default:
194             CHECK(false);
195     }
196 }
197 
198 }  // namespace aidl::android::hardware::neuralnetworks::vts::functional
199