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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 #define LOG_TAG "Memory"
18 
19 #include "Memory.h"
20 
21 #include "ExecutionBurstController.h"
22 #include "HalInterfaces.h"
23 #include "Utils.h"
24 
25 namespace android {
26 namespace nn {
27 
~Memory()28 Memory::~Memory() {
29     for (const auto [ptr, weakBurst] : mUsedBy) {
30         if (const std::shared_ptr<ExecutionBurstController> burst = weakBurst.lock()) {
31             burst->freeMemory(getKey());
32         }
33     }
34 }
35 
create(uint32_t size)36 int Memory::create(uint32_t size) {
37     mHidlMemory = allocateSharedMemory(size);
38     mMemory = mapMemory(mHidlMemory);
39     if (mMemory == nullptr) {
40         LOG(ERROR) << "Memory::create failed";
41         return ANEURALNETWORKS_OUT_OF_MEMORY;
42     }
43     return ANEURALNETWORKS_NO_ERROR;
44 }
45 
validateSize(uint32_t offset,uint32_t length) const46 bool Memory::validateSize(uint32_t offset, uint32_t length) const {
47     if (offset + length > mHidlMemory.size()) {
48         LOG(ERROR) << "Request size larger than the memory size.";
49         return false;
50     } else {
51         return true;
52     }
53 }
54 
getKey() const55 intptr_t Memory::getKey() const {
56     return reinterpret_cast<intptr_t>(this);
57 }
58 
usedBy(const std::shared_ptr<ExecutionBurstController> & burst) const59 void Memory::usedBy(const std::shared_ptr<ExecutionBurstController>& burst) const {
60     std::lock_guard<std::mutex> guard(mMutex);
61     mUsedBy.emplace(burst.get(), burst);
62 }
63 
~MemoryFd()64 MemoryFd::~MemoryFd() {
65     // Unmap the memory.
66     if (mMapping) {
67         munmap(mMapping, mHidlMemory.size());
68     }
69     // Delete the native_handle.
70     if (mHandle) {
71         int fd = mHandle->data[0];
72         if (fd != -1) {
73             close(fd);
74         }
75         native_handle_delete(mHandle);
76     }
77 }
78 
set(size_t size,int prot,int fd,size_t offset)79 int MemoryFd::set(size_t size, int prot, int fd, size_t offset) {
80     if (size == 0 || fd < 0) {
81         LOG(ERROR) << "Invalid size or fd";
82         return ANEURALNETWORKS_BAD_DATA;
83     }
84     int dupfd = dup(fd);
85     if (dupfd == -1) {
86         LOG(ERROR) << "Failed to dup the fd";
87         return ANEURALNETWORKS_UNEXPECTED_NULL;
88     }
89 
90     if (mMapping) {
91         if (munmap(mMapping, mHidlMemory.size()) != 0) {
92             LOG(ERROR) << "Failed to remove the existing mapping";
93             // This is not actually fatal.
94         }
95         mMapping = nullptr;
96     }
97     if (mHandle) {
98         native_handle_delete(mHandle);
99     }
100     mHandle = native_handle_create(1, 3);
101     if (mHandle == nullptr) {
102         LOG(ERROR) << "Failed to create native_handle";
103         return ANEURALNETWORKS_UNEXPECTED_NULL;
104     }
105     mHandle->data[0] = dupfd;
106     mHandle->data[1] = prot;
107     mHandle->data[2] = (int32_t)(uint32_t)(offset & 0xffffffff);
108 #if defined(__LP64__)
109     mHandle->data[3] = (int32_t)(uint32_t)(offset >> 32);
110 #else
111     mHandle->data[3] = 0;
112 #endif
113     mHidlMemory = hidl_memory("mmap_fd", mHandle, size);
114     return ANEURALNETWORKS_NO_ERROR;
115 }
116 
getPointer(uint8_t ** buffer) const117 int MemoryFd::getPointer(uint8_t** buffer) const {
118     if (mMapping) {
119         *buffer = mMapping;
120         return ANEURALNETWORKS_NO_ERROR;
121     }
122 
123     if (mHandle == nullptr) {
124         LOG(ERROR) << "Memory not initialized";
125         return ANEURALNETWORKS_UNEXPECTED_NULL;
126     }
127 
128     int fd = mHandle->data[0];
129     int prot = mHandle->data[1];
130     size_t offset = getSizeFromInts(mHandle->data[2], mHandle->data[3]);
131     void* data = mmap(nullptr, mHidlMemory.size(), prot, MAP_SHARED, fd, offset);
132     if (data == MAP_FAILED) {
133         LOG(ERROR) << "MemoryFd::getPointer(): Can't mmap the file descriptor.";
134         return ANEURALNETWORKS_UNMAPPABLE;
135     } else {
136         mMapping = *buffer = static_cast<uint8_t*>(data);
137         return ANEURALNETWORKS_NO_ERROR;
138     }
139 }
140 
add(const Memory * memory)141 uint32_t MemoryTracker::add(const Memory* memory) {
142     VLOG(MODEL) << __func__ << "(" << SHOW_IF_DEBUG(memory) << ")";
143     // See if we already have this memory. If so,
144     // return its index.
145     auto i = mKnown.find(memory);
146     if (i != mKnown.end()) {
147         return i->second;
148     }
149     VLOG(MODEL) << "It's new";
150     // It's a new one.  Save it an assign an index to it.
151     size_t next = mKnown.size();
152     if (next > 0xFFFFFFFF) {
153         LOG(ERROR) << "ANeuralNetworks more than 2^32 memories.";
154         return ANEURALNETWORKS_BAD_DATA;
155     }
156     uint32_t idx = static_cast<uint32_t>(next);
157     mKnown[memory] = idx;
158     mMemories.push_back(memory);
159     return idx;
160 }
161 
162 } // namespace nn
163 } // namespace android
164