1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
|
/*
* Copyright (C) 2021 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_aidl_hal_test"
#include "VtsHalNeuralnetworks.h"
#include <android-base/logging.h>
#include <android/binder_auto_utils.h>
#include <android/binder_interface_utils.h>
#include <android/binder_manager.h>
#include <android/binder_status.h>
#include <gtest/gtest.h>
#include <memory>
#include <string>
#include <utility>
#include <TestHarness.h>
#include <aidl/Vintf.h>
#include <nnapi/hal/aidl/Conversions.h>
#include "Callbacks.h"
#include "GeneratedTestHarness.h"
#include "Utils.h"
namespace aidl::android::hardware::neuralnetworks::vts::functional {
using implementation::PreparedModelCallback;
// internal helper function
void createPreparedModel(const std::shared_ptr<IDevice>& device, const Model& model,
std::shared_ptr<IPreparedModel>* preparedModel, bool reportSkipping) {
ASSERT_NE(nullptr, preparedModel);
*preparedModel = nullptr;
// see if service can handle model
std::vector<bool> supportedOperations;
const auto supportedCallStatus = device->getSupportedOperations(model, &supportedOperations);
ASSERT_TRUE(supportedCallStatus.isOk());
ASSERT_NE(0ul, supportedOperations.size());
const bool fullySupportsModel = std::all_of(
supportedOperations.begin(), supportedOperations.end(), [](bool v) { return v; });
// launch prepare model
const std::shared_ptr<PreparedModelCallback> preparedModelCallback =
ndk::SharedRefBase::make<PreparedModelCallback>();
const auto prepareLaunchStatus =
device->prepareModel(model, ExecutionPreference::FAST_SINGLE_ANSWER, kDefaultPriority,
kNoDeadline, {}, {}, kEmptyCacheToken, preparedModelCallback);
ASSERT_TRUE(prepareLaunchStatus.isOk()) << prepareLaunchStatus.getDescription();
// retrieve prepared model
preparedModelCallback->wait();
const ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
*preparedModel = preparedModelCallback->getPreparedModel();
// The getSupportedOperations call returns a list of operations that are guaranteed not to fail
// if prepareModel is called, and 'fullySupportsModel' is true i.f.f. the entire model is
// guaranteed. If a driver has any doubt that it can prepare an operation, it must return false.
// So here, if a driver isn't sure if it can support an operation, but reports that it
// successfully prepared the model, the test can continue.
if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
ASSERT_EQ(nullptr, preparedModel->get());
if (!reportSkipping) {
return;
}
LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot prepare "
"model that it does not support.";
std::cout << "[ ] Early termination of test because vendor service cannot "
"prepare model that it does not support."
<< std::endl;
GTEST_SKIP();
}
ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel->get());
}
void NeuralNetworksAidlTest::SetUp() {
testing::TestWithParam<NeuralNetworksAidlTestParam>::SetUp();
ASSERT_NE(kDevice, nullptr);
const bool deviceIsResponsive =
ndk::ScopedAStatus::fromStatus(AIBinder_ping(kDevice->asBinder().get())).isOk();
ASSERT_TRUE(deviceIsResponsive);
}
static NamedDevice makeNamedDevice(const std::string& name) {
ndk::SpAIBinder binder(AServiceManager_waitForService(name.c_str()));
return {name, IDevice::fromBinder(binder)};
}
static std::vector<NamedDevice> getNamedDevicesImpl() {
// Retrieves the name of all service instances that implement IDevice,
// including any Lazy HAL instances.
const std::vector<std::string> names = ::android::getAidlHalInstanceNames(IDevice::descriptor);
// Get a handle to each device and pair it with its name.
std::vector<NamedDevice> namedDevices;
namedDevices.reserve(names.size());
std::transform(names.begin(), names.end(), std::back_inserter(namedDevices), makeNamedDevice);
return namedDevices;
}
const std::vector<NamedDevice>& getNamedDevices() {
const static std::vector<NamedDevice> devices = getNamedDevicesImpl();
return devices;
}
std::string printNeuralNetworksAidlTest(
const testing::TestParamInfo<NeuralNetworksAidlTestParam>& info) {
return gtestCompliantName(getName(info.param));
}
INSTANTIATE_DEVICE_TEST(NeuralNetworksAidlTest);
// Forward declaration from ValidateModel.cpp
void validateModel(const std::shared_ptr<IDevice>& device, const Model& model);
// Forward declaration from ValidateRequest.cpp
void validateRequest(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request);
// Forward declaration from ValidateRequest.cpp
void validateBurst(const std::shared_ptr<IPreparedModel>& preparedModel, const Request& request);
// Forward declaration from ValidateRequest.cpp
void validateRequestFailure(const std::shared_ptr<IPreparedModel>& preparedModel,
const Request& request);
void validateEverything(const std::shared_ptr<IDevice>& device, const Model& model,
const Request& request) {
validateModel(device, model);
// Create IPreparedModel.
std::shared_ptr<IPreparedModel> preparedModel;
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
validateRequest(preparedModel, request);
validateBurst(preparedModel, request);
// HIDL also had test that expected executeFenced to fail on received null fd (-1). This is not
// allowed in AIDL and will result in EX_TRANSACTION_FAILED.
}
void validateFailure(const std::shared_ptr<IDevice>& device, const Model& model,
const Request& request) {
// TODO: Should this always succeed?
// What if the invalid input is part of the model (i.e., a parameter).
validateModel(device, model);
// Create IPreparedModel.
std::shared_ptr<IPreparedModel> preparedModel;
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
validateRequestFailure(preparedModel, request);
}
TEST_P(ValidationTest, Test) {
const Model model = createModel(kTestModel);
ExecutionContext context;
const Request request = context.createRequest(kTestModel);
if (kTestModel.expectFailure) {
validateFailure(kDevice, model, request);
} else {
validateEverything(kDevice, model, request);
}
}
INSTANTIATE_GENERATED_TEST(ValidationTest, [](const std::string& testName) {
// Skip validation for the "inputs_as_internal" and "all_tensors_as_inputs"
// generated tests.
return testName.find("inputs_as_internal") == std::string::npos &&
testName.find("all_tensors_as_inputs") == std::string::npos;
});
std::string toString(Executor executor) {
switch (executor) {
case Executor::SYNC:
return "SYNC";
case Executor::BURST:
return "BURST";
case Executor::FENCED:
return "FENCED";
default:
CHECK(false);
}
}
} // namespace aidl::android::hardware::neuralnetworks::vts::functional
|
