1 /*
2  * Copyright (C) 2018 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 // This test only tests internal APIs, and has dependencies on internal header
18 // files, including NN API HIDL definitions.
19 // It is not part of CTS.
20 
21 #include "TestMemory.h"
22 
23 #include "Manager.h"
24 #include "Memory.h"
25 #include "TestNeuralNetworksWrapper.h"
26 
27 #include <android/sharedmem.h>
28 #include <gtest/gtest.h>
29 
30 #include <fstream>
31 #include <string>
32 
33 using WrapperCompilation = ::android::nn::test_wrapper::Compilation;
34 using WrapperExecution = ::android::nn::test_wrapper::Execution;
35 using WrapperMemory = ::android::nn::test_wrapper::Memory;
36 using WrapperModel = ::android::nn::test_wrapper::Model;
37 using WrapperOperandType = ::android::nn::test_wrapper::OperandType;
38 using WrapperResult = ::android::nn::test_wrapper::Result;
39 using WrapperType = ::android::nn::test_wrapper::Type;
40 
41 namespace {
42 
43 // Tests to ensure that various kinds of memory leaks do not occur.
44 //
45 // The fixture checks that no anonymous shared memory regions are leaked by
46 // comparing the count of /dev/ashmem mappings in SetUp and TearDown. This could
47 // break if the test or framework starts lazily instantiating something that
48 // creates a mapping - at that point the way the test works needs to be
49 // reinvestigated. The filename /dev/ashmem is a documented part of the Android
50 // kernel interface (see
51 // https://source.android.com/devices/architecture/kernel/reqs-interfaces).
52 //
53 // (We can also get very unlucky and mask a memory leak by unrelated unmapping
54 // somewhere else. This seems unlikely enough to not deal with.)
55 class MemoryLeakTest : public ::testing::Test {
56 protected:
57     void SetUp() override;
58     void TearDown() override;
59 
60 private:
61     size_t GetAshmemMappingsCount();
62 
63     size_t mStartingMapCount = 0;
64     bool mIsCpuOnly;
65 };
66 
SetUp()67 void MemoryLeakTest::SetUp() {
68     mIsCpuOnly = android::nn::DeviceManager::get()->getUseCpuOnly();
69     mStartingMapCount = GetAshmemMappingsCount();
70 }
71 
TearDown()72 void MemoryLeakTest::TearDown() {
73     android::nn::DeviceManager::get()->setUseCpuOnly(mIsCpuOnly);
74     const size_t endingMapCount = GetAshmemMappingsCount();
75     ASSERT_EQ(mStartingMapCount, endingMapCount);
76 }
77 
GetAshmemMappingsCount()78 size_t MemoryLeakTest::GetAshmemMappingsCount() {
79     std::ifstream mappingsStream("/proc/self/maps");
80     if (! mappingsStream.good()) {
81         // errno is set by std::ifstream on Linux
82         ADD_FAILURE() << "Failed to open /proc/self/maps: " << std::strerror(errno);
83         return 0;
84     }
85     std::string line;
86     int mapCount = 0;
87     while (std::getline(mappingsStream, line)) {
88       if (line.find("/dev/ashmem") != std::string::npos) {
89         ++mapCount;
90       }
91     }
92     return mapCount;
93 }
94 
95 // As well as serving as a functional test for ASharedMemory, also
96 // serves as a regression test for http://b/69685100 "RunTimePoolInfo
97 // leaks shared memory regions".
98 //
99 // TODO: test non-zero offset.
TEST_F(MemoryLeakTest,TestASharedMemory)100 TEST_F(MemoryLeakTest, TestASharedMemory) {
101     // Layout where to place matrix2 and matrix3 in the memory we'll allocate.
102     // We have gaps to test that we don't assume contiguity.
103     constexpr uint32_t offsetForMatrix2 = 20;
104     constexpr uint32_t offsetForMatrix3 = offsetForMatrix2 + sizeof(matrix2) + 30;
105     constexpr uint32_t weightsSize = offsetForMatrix3 + sizeof(matrix3) + 60;
106 
107     int weightsFd = ASharedMemory_create("weights", weightsSize);
108     ASSERT_GT(weightsFd, -1);
109     uint8_t* weightsData = (uint8_t*)mmap(nullptr, weightsSize, PROT_READ | PROT_WRITE,
110                                           MAP_SHARED, weightsFd, 0);
111     ASSERT_NE(weightsData, nullptr);
112     memcpy(weightsData + offsetForMatrix2, matrix2, sizeof(matrix2));
113     memcpy(weightsData + offsetForMatrix3, matrix3, sizeof(matrix3));
114     WrapperMemory weights(weightsSize, PROT_READ | PROT_WRITE, weightsFd, 0);
115     ASSERT_TRUE(weights.isValid());
116 
117     WrapperModel model;
118     WrapperOperandType matrixType(WrapperType::TENSOR_FLOAT32, {3, 4});
119     WrapperOperandType scalarType(WrapperType::INT32, {});
120     int32_t activation(0);
121     auto a = model.addOperand(&matrixType);
122     auto b = model.addOperand(&matrixType);
123     auto c = model.addOperand(&matrixType);
124     auto d = model.addOperand(&matrixType);
125     auto e = model.addOperand(&matrixType);
126     auto f = model.addOperand(&scalarType);
127 
128     model.setOperandValueFromMemory(e, &weights, offsetForMatrix2, sizeof(Matrix3x4));
129     model.setOperandValueFromMemory(a, &weights, offsetForMatrix3, sizeof(Matrix3x4));
130     model.setOperandValue(f, &activation, sizeof(activation));
131     model.addOperation(ANEURALNETWORKS_ADD, {a, c, f}, {b});
132     model.addOperation(ANEURALNETWORKS_ADD, {b, e, f}, {d});
133     model.identifyInputsAndOutputs({c}, {d});
134     ASSERT_TRUE(model.isValid());
135     model.finish();
136 
137     // Test the two node model.
138     constexpr uint32_t offsetForMatrix1 = 20;
139     constexpr size_t inputSize = offsetForMatrix1 + sizeof(Matrix3x4);
140     int inputFd = ASharedMemory_create("input", inputSize);
141     ASSERT_GT(inputFd, -1);
142     uint8_t* inputData = (uint8_t*)mmap(nullptr, inputSize,
143                                         PROT_READ | PROT_WRITE, MAP_SHARED, inputFd, 0);
144     ASSERT_NE(inputData, nullptr);
145     memcpy(inputData + offsetForMatrix1, matrix1, sizeof(Matrix3x4));
146     WrapperMemory input(inputSize, PROT_READ, inputFd, 0);
147     ASSERT_TRUE(input.isValid());
148 
149     constexpr uint32_t offsetForActual = 32;
150     constexpr size_t outputSize = offsetForActual + sizeof(Matrix3x4);
151     int outputFd = ASharedMemory_create("output", outputSize);
152     ASSERT_GT(outputFd, -1);
153     uint8_t* outputData = (uint8_t*)mmap(nullptr, outputSize,
154                                          PROT_READ | PROT_WRITE, MAP_SHARED, outputFd, 0);
155     ASSERT_NE(outputData, nullptr);
156     memset(outputData, 0, outputSize);
157     WrapperMemory actual(outputSize, PROT_READ | PROT_WRITE, outputFd, 0);
158     ASSERT_TRUE(actual.isValid());
159 
160     WrapperCompilation compilation2(&model);
161     ASSERT_EQ(compilation2.finish(), WrapperResult::NO_ERROR);
162 
163     WrapperExecution execution2(&compilation2);
164     ASSERT_EQ(execution2.setInputFromMemory(0, &input, offsetForMatrix1, sizeof(Matrix3x4)),
165               WrapperResult::NO_ERROR);
166     ASSERT_EQ(execution2.setOutputFromMemory(0, &actual, offsetForActual, sizeof(Matrix3x4)),
167               WrapperResult::NO_ERROR);
168     ASSERT_EQ(execution2.compute(), WrapperResult::NO_ERROR);
169     ASSERT_EQ(CompareMatrices(expected3,
170                               *reinterpret_cast<Matrix3x4*>(outputData + offsetForActual)), 0);
171 
172     munmap(weightsData, weightsSize);
173     munmap(inputData, inputSize);
174     munmap(outputData, outputSize);
175     close(weightsFd);
176     close(inputFd);
177     close(outputFd);
178 }
179 
180 // Regression test for http://b/69621433 "MemoryFd leaks shared memory regions".
TEST_F(MemoryLeakTest,GetPointer)181 TEST_F(MemoryLeakTest, GetPointer) {
182     static const size_t size = 1;
183 
184     int fd = ASharedMemory_create(nullptr, size);
185     ASSERT_GE(fd, 0);
186 
187     uint8_t* buf = (uint8_t*)mmap(nullptr, size, PROT_READ | PROT_WRITE, MAP_SHARED, fd, 0);
188     ASSERT_NE(buf, nullptr);
189     *buf = 0;
190 
191     {
192         // Scope "mem" in such a way that any shared memory regions it
193         // owns will be released before we check the value of *buf: We
194         // want to verify that the explicit mmap() above is not
195         // perturbed by any mmap()/munmap() that results from methods
196         // invoked on "mem".
197 
198         WrapperMemory mem(size, PROT_READ | PROT_WRITE, fd, 0);
199         ASSERT_TRUE(mem.isValid());
200 
201         auto internalMem = reinterpret_cast<::android::nn::Memory*>(mem.get());
202         uint8_t *dummy;
203         ASSERT_EQ(internalMem->getPointer(&dummy), ANEURALNETWORKS_NO_ERROR);
204         (*dummy)++;
205     }
206 
207     ASSERT_EQ(*buf, (uint8_t)1);
208     ASSERT_EQ(munmap(buf, size), 0);
209 
210     close(fd);
211 }
212 
213 // Regression test for http://b/69621433 "MemoryFd leaks shared memory regions".
TEST_F(MemoryLeakTest,Instantiate)214 TEST_F(MemoryLeakTest, Instantiate) {
215     static const size_t size = 1;
216     int fd = ASharedMemory_create(nullptr, size);
217     ASSERT_GE(fd, 0);
218     WrapperMemory mem(size, PROT_READ | PROT_WRITE, fd, 0);
219     ASSERT_TRUE(mem.isValid());
220 
221     auto internalMem = reinterpret_cast<::android::nn::Memory*>(mem.get());
222     uint8_t *dummy;
223     ASSERT_EQ(internalMem->getPointer(&dummy), ANEURALNETWORKS_NO_ERROR);
224 
225     close(fd);
226 }
227 
228 #ifndef NNTEST_ONLY_PUBLIC_API
229 // Regression test for http://b/73663843, conv_2d trying to allocate too much memory.
TEST_F(MemoryLeakTest,convTooLarge)230 TEST_F(MemoryLeakTest, convTooLarge) {
231     android::nn::DeviceManager::get()->setUseCpuOnly(true);
232     WrapperModel model;
233 
234     // This kernel/input size will make convQuant8 allocate 12 * 13 * 13 * 128 * 92 * 92, which is
235     // just outside of signed int range (0x82F56000) - this will fail due to CPU implementation
236     // limitations
237     WrapperOperandType type3(WrapperType::INT32, {});
238     WrapperOperandType type2(WrapperType::TENSOR_INT32, {128}, 0.25, 0);
239     WrapperOperandType type0(WrapperType::TENSOR_QUANT8_ASYMM, {12, 104, 104, 128}, 0.5, 0);
240     WrapperOperandType type4(WrapperType::TENSOR_QUANT8_ASYMM, {12, 92, 92, 128}, 1.0, 0);
241     WrapperOperandType type1(WrapperType::TENSOR_QUANT8_ASYMM, {128, 13, 13, 128}, 0.5, 0);
242 
243     // Operands
244     auto op1 = model.addOperand(&type0);
245     auto op2 = model.addOperand(&type1);
246     auto op3 = model.addOperand(&type2);
247     auto pad0 = model.addOperand(&type3);
248     auto act = model.addOperand(&type3);
249     auto stride = model.addOperand(&type3);
250     auto op4 = model.addOperand(&type4);
251 
252     // Operations
253     uint8_t op2_init[128 * 13 * 13 * 128] = {};
254     model.setOperandValue(op2, op2_init, sizeof(op2_init));
255     int32_t op3_init[128] = {};
256     model.setOperandValue(op3, op3_init, sizeof(op3_init));
257     int32_t pad0_init[] = {0};
258     model.setOperandValue(pad0, pad0_init, sizeof(pad0_init));
259     int32_t act_init[] = {0};
260     model.setOperandValue(act, act_init, sizeof(act_init));
261     int32_t stride_init[] = {1};
262     model.setOperandValue(stride, stride_init, sizeof(stride_init));
263     model.addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
264 
265     // Inputs and outputs
266     model.identifyInputsAndOutputs({op1}, {op4});
267     ASSERT_TRUE(model.isValid());
268     model.finish();
269 
270     // Compilation
271     WrapperCompilation compilation(&model);
272     ASSERT_EQ(WrapperResult::NO_ERROR,compilation.finish());
273     WrapperExecution execution(&compilation);
274 
275     // Set input and outputs
276     static uint8_t input[12 * 104 * 104 * 128] = {};
277     ASSERT_EQ(WrapperResult::NO_ERROR, execution.setInput(0, input, sizeof(input)));
278     static uint8_t output[12 * 92 * 92 * 128] = {};
279     ASSERT_EQ(WrapperResult::NO_ERROR, execution.setOutput(0, output, sizeof(output)));
280 
281     // This shouldn't segfault
282     WrapperResult r = execution.compute();
283 
284     ASSERT_EQ(WrapperResult::OP_FAILED, r);
285 }
286 #endif // NNTEST_ONLY_PUBLIC_API
287 
288 }  // end namespace
289