1 /*
2 * Copyright (C) 2020 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 "GeneratedTestUtils.h"
18
19 #include <android-base/logging.h>
20 #include <gtest/gtest.h>
21
22 #include <algorithm>
23 #include <memory>
24 #include <string>
25 #include <utility>
26 #include <vector>
27
28 #include "TestHarness.h"
29
30 #ifdef NNTEST_SLTS
31 #include <android/hardware_buffer.h>
32 #include "SupportLibraryWrapper.h"
33 #else
34 #include "TestNeuralNetworksWrapper.h"
35 #endif
36
37 namespace android::nn::generated_tests {
38 using namespace test_wrapper;
39 using namespace test_helper;
40
getOperandType(const TestOperand & op,bool testDynamicOutputShape)41 static OperandType getOperandType(const TestOperand& op, bool testDynamicOutputShape) {
42 auto dims = op.dimensions;
43 if (testDynamicOutputShape && op.lifetime == TestOperandLifeTime::SUBGRAPH_OUTPUT) {
44 dims.assign(dims.size(), 0);
45 }
46 if (op.type == TestOperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL) {
47 return OperandType(
48 static_cast<Type>(op.type), dims,
49 SymmPerChannelQuantParams(op.channelQuant.scales, op.channelQuant.channelDim));
50 } else {
51 return OperandType(static_cast<Type>(op.type), dims, op.scale, op.zeroPoint);
52 }
53 }
54
55 // A Memory object that owns AHardwareBuffer
56 class MemoryAHWB : public Memory {
57 public:
58 #ifdef NNTEST_SLTS
create(const NnApiSupportLibrary * nnapi,uint32_t size)59 static std::unique_ptr<MemoryAHWB> create(const NnApiSupportLibrary* nnapi, uint32_t size) {
60 #else
61 static std::unique_ptr<MemoryAHWB> create(uint32_t size) {
62 #endif
63 const uint64_t usage =
64 AHARDWAREBUFFER_USAGE_CPU_READ_OFTEN | AHARDWAREBUFFER_USAGE_CPU_WRITE_OFTEN;
65 AHardwareBuffer_Desc desc = {
66 .width = size,
67 .height = 1,
68 .layers = 1,
69 .format = AHARDWAREBUFFER_FORMAT_BLOB,
70 .usage = usage,
71 };
72 AHardwareBuffer* ahwb = nullptr;
73 EXPECT_EQ(AHardwareBuffer_allocate(&desc, &ahwb), 0);
74 EXPECT_NE(ahwb, nullptr);
75
76 void* buffer = nullptr;
77 EXPECT_EQ(AHardwareBuffer_lock(ahwb, usage, -1, nullptr, &buffer), 0);
78 EXPECT_NE(buffer, nullptr);
79
80 #ifdef NNTEST_SLTS
81 return std::unique_ptr<MemoryAHWB>(new MemoryAHWB(nnapi, ahwb, buffer));
82 #else
83 return std::unique_ptr<MemoryAHWB>(new MemoryAHWB(ahwb, buffer));
84 #endif
85 }
86
87 ~MemoryAHWB() override {
88 EXPECT_EQ(AHardwareBuffer_unlock(mAhwb, nullptr), 0);
89 AHardwareBuffer_release(mAhwb);
90 }
91
92 void* getPointer() const { return mBuffer; }
93
94 private:
95 #ifdef NNTEST_SLTS
96 MemoryAHWB(const NnApiSupportLibrary* nnapi, AHardwareBuffer* ahwb, void* buffer)
97 : Memory(nnapi, ahwb, false, {}), mAhwb(ahwb), mBuffer(buffer) {}
98 #else
99 MemoryAHWB(AHardwareBuffer* ahwb, void* buffer) : Memory(ahwb), mAhwb(ahwb), mBuffer(buffer) {}
100 #endif
101
102 AHardwareBuffer* mAhwb;
103 void* mBuffer;
104 };
105
106 #ifdef NNTEST_SLTS
createConstantReferenceMemory(const NnApiSupportLibrary * nnapi,const TestModel & testModel)107 static std::unique_ptr<MemoryAHWB> createConstantReferenceMemory(const NnApiSupportLibrary* nnapi,
108 const TestModel& testModel) {
109 #else
110 static std::unique_ptr<MemoryAHWB> createConstantReferenceMemory(const TestModel& testModel) {
111 #endif
112 uint32_t size = 0;
113
114 auto processSubgraph = [&size](const TestSubgraph& subgraph) {
115 for (const TestOperand& operand : subgraph.operands) {
116 if (operand.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) {
117 size += operand.data.alignedSize();
118 }
119 }
120 };
121
122 processSubgraph(testModel.main);
123 for (const TestSubgraph& subgraph : testModel.referenced) {
124 processSubgraph(subgraph);
125 }
126 #ifdef NNTEST_SLTS
127 return size == 0 ? nullptr : MemoryAHWB::create(nnapi, size);
128 #else
129 return size == 0 ? nullptr : MemoryAHWB::create(size);
130 #endif
131 }
132
133 static void createModelFromSubgraph(const TestSubgraph& subgraph, bool testDynamicOutputShape,
134 const std::vector<TestSubgraph>& refSubgraphs,
135 const std::unique_ptr<MemoryAHWB>& memory,
136 uint32_t* memoryOffset, Model* model, Model* refModels) {
137 // Operands.
138 for (const auto& operand : subgraph.operands) {
139 auto type = getOperandType(operand, testDynamicOutputShape);
140 auto index = model->addOperand(&type);
141
142 switch (operand.lifetime) {
143 case TestOperandLifeTime::CONSTANT_COPY: {
144 model->setOperandValue(index, operand.data.get<void>(), operand.data.size());
145 } break;
146 case TestOperandLifeTime::CONSTANT_REFERENCE: {
147 const uint32_t length = operand.data.size();
148 std::memcpy(static_cast<uint8_t*>(memory->getPointer()) + *memoryOffset,
149 operand.data.get<void>(), length);
150 model->setOperandValueFromMemory(index, memory.get(), *memoryOffset, length);
151 *memoryOffset += operand.data.alignedSize();
152 } break;
153 case TestOperandLifeTime::NO_VALUE: {
154 model->setOperandValue(index, nullptr, 0);
155 } break;
156 case TestOperandLifeTime::SUBGRAPH: {
157 uint32_t refIndex = *operand.data.get<uint32_t>();
158 CHECK_LT(refIndex, refSubgraphs.size());
159 const TestSubgraph& refSubgraph = refSubgraphs[refIndex];
160 Model* refModel = &refModels[refIndex];
161
162 if (!refModel->isFinished()) {
163 createModelFromSubgraph(refSubgraph, testDynamicOutputShape, refSubgraphs,
164 memory, memoryOffset, refModel, refModels);
165 ASSERT_EQ(refModel->finish(), Result::NO_ERROR);
166 ASSERT_TRUE(refModel->isValid());
167 }
168 model->setOperandValueFromModel(index, refModel);
169 } break;
170 case TestOperandLifeTime::SUBGRAPH_INPUT:
171 case TestOperandLifeTime::SUBGRAPH_OUTPUT:
172 case TestOperandLifeTime::TEMPORARY_VARIABLE: {
173 // Nothing to do here.
174 } break;
175 }
176 }
177
178 // Operations.
179 for (const auto& operation : subgraph.operations) {
180 model->addOperation(static_cast<int>(operation.type), operation.inputs, operation.outputs);
181 }
182
183 // Inputs and outputs.
184 model->identifyInputsAndOutputs(subgraph.inputIndexes, subgraph.outputIndexes);
185 }
186
187 #ifdef NNTEST_SLTS
188 void createModel(const NnApiSupportLibrary* nnapi, const TestModel& testModel,
189 bool testDynamicOutputShape, GeneratedModel* model) {
190 #else
191 void createModel(const TestModel& testModel, bool testDynamicOutputShape, GeneratedModel* model) {
192 #endif
193 ASSERT_NE(nullptr, model);
194
195 #ifdef NNTEST_SLTS
196 std::unique_ptr<MemoryAHWB> memory = createConstantReferenceMemory(nnapi, testModel);
197 #else
198 std::unique_ptr<MemoryAHWB> memory = createConstantReferenceMemory(testModel);
199 #endif
200 uint32_t memoryOffset = 0;
201 #ifdef NNTEST_SLTS
202 std::vector<Model> refModels;
203 refModels.reserve(testModel.referenced.size());
204 for (int i = 0; i < testModel.referenced.size(); ++i) {
205 refModels.push_back(Model(nnapi));
206 }
207 #else
208 std::vector<Model> refModels(testModel.referenced.size());
209 #endif
210 createModelFromSubgraph(testModel.main, testDynamicOutputShape, testModel.referenced, memory,
211 &memoryOffset, model, refModels.data());
212 model->setRefModels(std::move(refModels));
213 model->setConstantReferenceMemory(std::move(memory));
214
215 // Relaxed computation.
216 model->relaxComputationFloat32toFloat16(testModel.isRelaxed);
217
218 if (!testModel.expectFailure) {
219 ASSERT_TRUE(model->isValid());
220 }
221 }
222
223 void createRequest(const TestModel& testModel, Execution* execution,
224 std::vector<TestBuffer>* outputs) {
225 ASSERT_NE(nullptr, execution);
226 ASSERT_NE(nullptr, outputs);
227
228 // Model inputs.
229 for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
230 const auto& operand = testModel.main.operands[testModel.main.inputIndexes[i]];
231 ASSERT_EQ(Result::NO_ERROR,
232 execution->setInput(i, operand.data.get<void>(), operand.data.size()));
233 }
234
235 // Model outputs.
236 for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) {
237 const auto& operand = testModel.main.operands[testModel.main.outputIndexes[i]];
238
239 // In the case of zero-sized output, we should at least provide a one-byte buffer.
240 // This is because zero-sized tensors are only supported internally to the runtime, or
241 // reported in output shapes. It is illegal for the client to pre-specify a zero-sized
242 // tensor as model output. Otherwise, we will have two semantic conflicts:
243 // - "Zero dimension" conflicts with "unspecified dimension".
244 // - "Omitted operand buffer" conflicts with "zero-sized operand buffer".
245 const size_t bufferSize = std::max<size_t>(operand.data.size(), 1);
246
247 outputs->emplace_back(bufferSize);
248 ASSERT_EQ(Result::NO_ERROR,
249 execution->setOutput(i, outputs->back().getMutable<void>(), bufferSize));
250 }
251 }
252
253 } // namespace android::nn::generated_tests
254