1 /*
2 * Copyright (C) 2017 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 #include "GeneratedTestHarness.h"
18
19 #include <android-base/logging.h>
20 #include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
21 #include <android/hardware/neuralnetworks/1.0/types.h>
22 #include <android/hardware/neuralnetworks/1.1/IDevice.h>
23 #include <android/hidl/allocator/1.0/IAllocator.h>
24 #include <android/hidl/memory/1.0/IMemory.h>
25 #include <hidlmemory/mapping.h>
26
27 #include <gtest/gtest.h>
28 #include <iostream>
29
30 #include "1.0/Callbacks.h"
31 #include "1.0/Utils.h"
32 #include "MemoryUtils.h"
33 #include "TestHarness.h"
34 #include "VtsHalNeuralnetworks.h"
35
36 namespace android::hardware::neuralnetworks::V1_1::vts::functional {
37
38 using namespace test_helper;
39 using hidl::memory::V1_0::IMemory;
40 using V1_0::DataLocation;
41 using V1_0::ErrorStatus;
42 using V1_0::IPreparedModel;
43 using V1_0::Operand;
44 using V1_0::OperandLifeTime;
45 using V1_0::OperandType;
46 using V1_0::Request;
47 using V1_0::implementation::ExecutionCallback;
48 using V1_0::implementation::PreparedModelCallback;
49
createModel(const TestModel & testModel)50 Model createModel(const TestModel& testModel) {
51 // Model operands.
52 CHECK_EQ(testModel.referenced.size(), 0u); // Not supported in 1.1.
53 hidl_vec<Operand> operands(testModel.main.operands.size());
54 size_t constCopySize = 0, constRefSize = 0;
55 for (uint32_t i = 0; i < testModel.main.operands.size(); i++) {
56 const auto& op = testModel.main.operands[i];
57
58 DataLocation loc = {};
59 if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) {
60 loc = {.poolIndex = 0,
61 .offset = static_cast<uint32_t>(constCopySize),
62 .length = static_cast<uint32_t>(op.data.size())};
63 constCopySize += op.data.alignedSize();
64 } else if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) {
65 loc = {.poolIndex = 0,
66 .offset = static_cast<uint32_t>(constRefSize),
67 .length = static_cast<uint32_t>(op.data.size())};
68 constRefSize += op.data.alignedSize();
69 }
70
71 operands[i] = {.type = static_cast<OperandType>(op.type),
72 .dimensions = op.dimensions,
73 .numberOfConsumers = op.numberOfConsumers,
74 .scale = op.scale,
75 .zeroPoint = op.zeroPoint,
76 .lifetime = static_cast<OperandLifeTime>(op.lifetime),
77 .location = loc};
78 }
79
80 // Model operations.
81 hidl_vec<Operation> operations(testModel.main.operations.size());
82 std::transform(testModel.main.operations.begin(), testModel.main.operations.end(),
83 operations.begin(), [](const TestOperation& op) -> Operation {
84 return {.type = static_cast<OperationType>(op.type),
85 .inputs = op.inputs,
86 .outputs = op.outputs};
87 });
88
89 // Constant copies.
90 hidl_vec<uint8_t> operandValues(constCopySize);
91 for (uint32_t i = 0; i < testModel.main.operands.size(); i++) {
92 const auto& op = testModel.main.operands[i];
93 if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) {
94 const uint8_t* begin = op.data.get<uint8_t>();
95 const uint8_t* end = begin + op.data.size();
96 std::copy(begin, end, operandValues.data() + operands[i].location.offset);
97 }
98 }
99
100 // Shared memory.
101 hidl_vec<hidl_memory> pools;
102 if (constRefSize > 0) {
103 hidl_vec_push_back(&pools, nn::allocateSharedMemory(constRefSize));
104 CHECK_NE(pools[0].size(), 0u);
105
106 // load data
107 sp<IMemory> mappedMemory = mapMemory(pools[0]);
108 CHECK(mappedMemory.get() != nullptr);
109 uint8_t* mappedPtr =
110 reinterpret_cast<uint8_t*>(static_cast<void*>(mappedMemory->getPointer()));
111 CHECK(mappedPtr != nullptr);
112
113 for (uint32_t i = 0; i < testModel.main.operands.size(); i++) {
114 const auto& op = testModel.main.operands[i];
115 if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) {
116 const uint8_t* begin = op.data.get<uint8_t>();
117 const uint8_t* end = begin + op.data.size();
118 std::copy(begin, end, mappedPtr + operands[i].location.offset);
119 }
120 }
121 }
122
123 return {.operands = std::move(operands),
124 .operations = std::move(operations),
125 .inputIndexes = testModel.main.inputIndexes,
126 .outputIndexes = testModel.main.outputIndexes,
127 .operandValues = std::move(operandValues),
128 .pools = std::move(pools),
129 .relaxComputationFloat32toFloat16 = testModel.isRelaxed};
130 }
131
132 // Top level driver for models and examples generated by test_generator.py
133 // Test driver for those generated from ml/nn/runtime/test/spec
Execute(const sp<IDevice> & device,const TestModel & testModel)134 void Execute(const sp<IDevice>& device, const TestModel& testModel) {
135 const Model model = createModel(testModel);
136
137 ExecutionContext context;
138 const Request request = context.createRequest(testModel);
139
140 // Create IPreparedModel.
141 sp<IPreparedModel> preparedModel;
142 createPreparedModel(device, model, &preparedModel);
143 if (preparedModel == nullptr) return;
144
145 // Launch execution.
146 sp<ExecutionCallback> executionCallback = new ExecutionCallback();
147 Return<ErrorStatus> executionLaunchStatus = preparedModel->execute(request, executionCallback);
148 ASSERT_TRUE(executionLaunchStatus.isOk());
149 EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
150
151 // Retrieve execution status.
152 executionCallback->wait();
153 ASSERT_EQ(ErrorStatus::NONE, executionCallback->getStatus());
154
155 // Retrieve execution results.
156 const std::vector<TestBuffer> outputs = context.getOutputBuffers(request);
157
158 // We want "close-enough" results.
159 checkResults(testModel, outputs);
160 }
161
SetUp()162 void GeneratedTestBase::SetUp() {
163 testing::TestWithParam<GeneratedTestParam>::SetUp();
164 ASSERT_NE(kDevice, nullptr);
165 const bool deviceIsResponsive = kDevice->ping().isOk();
166 ASSERT_TRUE(deviceIsResponsive);
167 }
168
getNamedModels(const FilterFn & filter)169 std::vector<NamedModel> getNamedModels(const FilterFn& filter) {
170 return TestModelManager::get().getTestModels(filter);
171 }
172
getNamedModels(const FilterNameFn & filter)173 std::vector<NamedModel> getNamedModels(const FilterNameFn& filter) {
174 return TestModelManager::get().getTestModels(filter);
175 }
176
printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam> & info)177 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info) {
178 const auto& [namedDevice, namedModel] = info.param;
179 return gtestCompliantName(getName(namedDevice) + "_" + getName(namedModel));
180 }
181
182 // Tag for the generated tests
183 class GeneratedTest : public GeneratedTestBase {};
184
TEST_P(GeneratedTest,Test)185 TEST_P(GeneratedTest, Test) {
186 Execute(kDevice, kTestModel);
187 }
188
189 INSTANTIATE_GENERATED_TEST(GeneratedTest,
__anonaf337bef0202(const TestModel& testModel) 190 [](const TestModel& testModel) { return !testModel.expectFailure; });
191
192 } // namespace android::hardware::neuralnetworks::V1_1::vts::functional
193