forked from ROCm/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
common.h
234 lines (204 loc) · 6.61 KB
/
common.h
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
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
#ifndef CAFFE2_CORE_COMMON_H_
#define CAFFE2_CORE_COMMON_H_
#include <algorithm>
#include <cmath>
#include <map>
#include <memory>
#include <numeric>
#include <set>
#include <sstream>
#include <string>
#include <type_traits>
#include <vector>
#ifdef __APPLE__
#include <TargetConditionals.h>
#endif
#if defined(_MSC_VER)
#include <io.h>
#else
#include <unistd.h>
#endif
// Macros used during the build of this caffe2 instance. This header file
// is automatically generated by the cmake script during build.
#include "caffe2/core/common.h"
#include "caffe2/core/macros.h"
#include "c10/macros/Macros.h"
namespace caffe2 {
// Note(Yangqing): NVCC does not play well with unordered_map on some platforms,
// forcing us to use std::map instead of unordered_map. This may affect speed
// in some cases, but in most of the computation code we do not access map very
// often, so it should be fine for us. I am putting a CaffeMap alias so we can
// change it more easily if things work out for unordered_map down the road.
template <typename Key, typename Value>
using CaffeMap = std::map<Key, Value>;
// using CaffeMap = std::unordered_map;
// Using statements for common classes that we refer to in caffe2 very often.
// Note that we only place it inside caffe2 so the global namespace is not
// polluted.
/* using override */
using std::set;
using std::string;
using std::unique_ptr;
using std::vector;
// Just in order to mark things as not implemented. Do not use in final code.
#define CAFFE_NOT_IMPLEMENTED CAFFE_THROW("Not Implemented.")
// suppress an unused variable.
#ifdef _MSC_VER
#define CAFFE2_UNUSED
#define CAFFE2_USED
#else
#define CAFFE2_UNUSED __attribute__((__unused__))
#define CAFFE2_USED __attribute__((__used__))
#endif //_MSC_VER
// Define enabled when building for iOS or Android devices
#if !defined(CAFFE2_MOBILE)
#if defined(__ANDROID__)
#define CAFFE2_ANDROID 1
#define CAFFE2_MOBILE 1
#elif (defined(__APPLE__) && \
(TARGET_IPHONE_SIMULATOR || TARGET_OS_SIMULATOR || TARGET_OS_IPHONE))
#define CAFFE2_IOS 1
#define CAFFE2_MOBILE 1
#elif (defined(__APPLE__) && TARGET_OS_MAC)
#define CAFFE2_IOS 1
#define CAFFE2_MOBILE 0
#else
#define CAFFE2_MOBILE 0
#endif // ANDROID / IOS / MACOS
#endif // CAFFE2_MOBILE
// Define alignment macro that is cross platform
#if defined(_MSC_VER)
#define CAFFE2_ALIGNED(x) __declspec(align(x))
#else
#define CAFFE2_ALIGNED(x) __attribute__((aligned(x)))
#endif
#if defined(_MSC_VER)
#define CAFFE2_NORETURN __declspec(noreturn)
#else
#define CAFFE2_NORETURN __attribute__((noreturn))
#endif
#if defined(_MSC_VER)
#define NOMINMAX
#endif
// make_unique is a C++14 feature. If we don't have 14, we will emulate
// its behavior. This is copied from folly/Memory.h
#if __cplusplus >= 201402L || \
(defined __cpp_lib_make_unique && __cpp_lib_make_unique >= 201304L) || \
(defined(_MSC_VER) && _MSC_VER >= 1900)
/* using override */
using std::make_unique;
#else
template<typename T, typename... Args>
typename std::enable_if<!std::is_array<T>::value, std::unique_ptr<T>>::type
make_unique(Args&&... args) {
return std::unique_ptr<T>(new T(std::forward<Args>(args)...));
}
// Allows 'make_unique<T[]>(10)'. (N3690 s20.9.1.4 p3-4)
template<typename T>
typename std::enable_if<std::is_array<T>::value, std::unique_ptr<T>>::type
make_unique(const size_t n) {
return std::unique_ptr<T>(new typename std::remove_extent<T>::type[n]());
}
// Disallows 'make_unique<T[10]>()'. (N3690 s20.9.1.4 p5)
template<typename T, typename... Args>
typename std::enable_if<
std::extent<T>::value != 0, std::unique_ptr<T>>::type
make_unique(Args&&...) = delete;
#endif
// to_string, stoi and stod implementation for Android related stuff.
// Note(jiayq): Do not use the CAFFE2_TESTONLY_FORCE_STD_STRING_TEST macro
// outside testing code that lives under common_test.cc
#if defined(__ANDROID__) || defined(CAFFE2_TESTONLY_FORCE_STD_STRING_TEST)
#define CAFFE2_TESTONLY_WE_ARE_USING_CUSTOM_STRING_FUNCTIONS 1
template <typename T>
std::string to_string(T value)
{
std::ostringstream os;
os << value;
return os.str();
}
inline int stoi(const string& str) {
std::stringstream ss;
int n = 0;
ss << str;
ss >> n;
return n;
}
inline double stod(const string& str, std::size_t* pos = 0) {
std::stringstream ss;
ss << str;
double val = 0;
ss >> val;
if (pos) {
if (ss.tellg() == std::streampos(-1)) {
*pos = str.size();
} else {
*pos = ss.tellg();
}
}
return val;
}
#else
#define CAFFE2_TESTONLY_WE_ARE_USING_CUSTOM_STRING_FUNCTIONS 0
using std::to_string;
using std::stoi;
using std::stod;
#endif // defined(__ANDROID__) || defined(CAFFE2_FORCE_STD_STRING_FALLBACK_TEST)
#if defined(__ANDROID__) && !defined(__NDK_MAJOR__)
using ::round;
#else
using std::round;
#endif // defined(__ANDROID__) && !defined(__NDK_MAJOR__)
// dynamic cast reroute: if RTTI is disabled, go to reinterpret_cast
template <typename Dst, typename Src>
inline Dst dynamic_cast_if_rtti(Src ptr) {
#ifdef __GXX_RTTI
return dynamic_cast<Dst>(ptr);
#else
return static_cast<Dst>(ptr);
#endif
}
// SkipIndices are used in operator_fallback_gpu.h and operator_fallback_mkl.h
// as utilty functions that marks input / output indices to skip when we use a
// CPU operator as the fallback of GPU/MKL operator option.
template <int... values>
class SkipIndices {
private:
template <int V>
static inline bool ContainsInternal(const int i) {
return (i == V);
}
template <int First, int Second, int... Rest>
static inline bool ContainsInternal(const int i) {
return (i == First) || ContainsInternal<Second, Rest...>(i);
}
public:
static inline bool Contains(const int i) {
return ContainsInternal<values...>(i);
}
};
template <>
class SkipIndices<> {
public:
static inline bool Contains(const int /*i*/) {
return false;
}
};
// HasCudaRuntime() tells the program whether the binary has Cuda runtime
// linked. This function should not be used in static initialization functions
// as the underlying boolean variable is going to be switched on when one
// loads libcaffe2_gpu.so.
CAFFE2_API bool HasCudaRuntime();
CAFFE2_API bool HasHipRuntime();
namespace internal {
// Sets the Cuda Runtime flag that is used by HasCudaRuntime(). You should
// never use this function - it is only used by the Caffe2 gpu code to notify
// Caffe2 core that cuda runtime has been loaded.
CAFFE2_API void SetCudaRuntimeFlag();
CAFFE2_API void SetHipRuntimeFlag();
}
// Returns which setting Caffe2 was configured and built with (exported from
// CMake)
CAFFE2_API const std::map<string, string>& GetBuildOptions();
} // namespace caffe2
#endif // CAFFE2_CORE_COMMON_H_