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
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
|
#include "caffe2/utils/math/transpose.h"
#include <algorithm>
#include <functional>
#include <limits>
#include <numeric>
#ifdef CAFFE2_USE_MKL
#include <mkl.h>
#endif // CAFFE2_USE_MKL
#ifdef CAFFE2_USE_HPTT
#include <hptt.h>
#endif // CAFFE2_USE_HPTT
#include "caffe2/core/context.h"
#include "caffe2/utils/eigen_utils.h"
#include "caffe2/utils/math/utils.h"
namespace caffe2 {
namespace math {
namespace {
template <typename TIndex, typename TData>
void Transpose2D(
const TIndex rows,
const TIndex cols,
const TData* X,
TData* Y) {
EigenMatrixMap<TData>(Y, rows, cols) =
ConstEigenMatrixMap<TData>(X, cols, rows).transpose();
}
#ifdef CAFFE2_USE_MKL
#define DELEGATE_TRANSPOSE_2D(TIndex, TData, MKLFunc) \
template <> \
void Transpose2D<TIndex, TData>( \
const TIndex rows, const TIndex cols, const TData* X, TData* Y) { \
MKLFunc('R', 'T', rows, cols, TData(1), X, cols, Y, rows); \
}
DELEGATE_TRANSPOSE_2D(std::int32_t, float, mkl_somatcopy);
DELEGATE_TRANSPOSE_2D(std::int64_t, float, mkl_somatcopy);
DELEGATE_TRANSPOSE_2D(std::int32_t, double, mkl_domatcopy);
DELEGATE_TRANSPOSE_2D(std::int64_t, double, mkl_domatcopy);
#undef DELEGATE_TRANSPOSE_2D
#endif // CAFFE2_USE_MKL
#ifdef CAFFE2_USE_HPTT
template <typename TIndex, typename TData>
bool TransposeByHPTT(
const int ndim,
const TIndex* dims,
const int* axes,
const TData* X,
TData* Y) {
for (int i = 0; i < ndim; ++i) {
if (dims[i] <= 0 || dims[i] > std::numeric_limits<int>::max()) {
return false;
}
}
std::vector<int> axes_cm(ndim);
std::vector<int> dims_cm(ndim);
// Convert row-major index to column-major.
const auto cm_fn = [ndim](const int i) { return ndim - i - 1; };
for (int i = 0; i < ndim; ++i) {
axes_cm[i] = cm_fn(axes[cm_fn(i)]);
dims_cm[i] = dims[cm_fn(i)];
}
auto plan = hptt::create_plan(
axes_cm.data(),
ndim,
TData(1),
X,
dims_cm.data(),
nullptr,
TData(0),
Y,
nullptr,
hptt::ESTIMATE,
1 /* num_threads */);
if (plan == nullptr) {
return false;
}
plan->execute();
return true;
}
#endif // CAFFE2_USE_HPTT
template <typename TIndex, typename TData>
void TransposeND(
const int ndim,
const TIndex* dims,
const int* axes,
const TData* X,
TData* Y) {
std::vector<TIndex> Y_dims(ndim);
for (int i = 0; i < ndim; ++i) {
Y_dims[i] = dims[axes[i]];
}
// Measure amount of contiguous data we can copy at once
int pivot = ndim - 1;
TIndex block_size = 1;
for (; pivot >= 0 && axes[pivot] == pivot; --pivot) {
block_size *= Y_dims[pivot];
}
++pivot;
const TIndex num_blocks = std::accumulate(
Y_dims.cbegin(),
Y_dims.cbegin() + pivot,
TIndex(1),
std::multiplies<TIndex>());
std::vector<TIndex> X_strides(pivot);
utils::ComputeTransposedStrides<TIndex>(pivot, dims, axes, X_strides.data());
std::vector<TIndex> index(pivot, 0);
for (TIndex Y_index = 0; Y_index < num_blocks; ++Y_index) {
const TIndex X_index = std::inner_product(
X_strides.cbegin(), X_strides.cend(), index.cbegin(), TIndex(0));
if (block_size == 1) {
Y[Y_index] = X[X_index];
} else {
std::memcpy(
Y + block_size * Y_index,
X + block_size * X_index,
block_size * sizeof(TData));
}
utils::IncreaseIndexInDims<TIndex>(pivot, Y_dims.data(), index.data());
}
}
template <typename TIndex, typename TData>
void TransposeImpl(
const int ndim,
const TIndex* dims,
const int* axes,
const TData* X,
TData* Y) {
const TIndex size =
std::accumulate(dims, dims + ndim, TIndex(1), std::multiplies<TIndex>());
if (size == 0) {
return;
}
if (utils::IsIdentityPermutation(ndim, axes)) {
std::memcpy(Y, X, size * sizeof(TData));
return;
}
if (utils::IsBatchTranspose2D(ndim, axes)) {
const TIndex H = dims[ndim - 2];
const TIndex W = dims[ndim - 1];
const TIndex N = size / (H * W);
for (TIndex i = 0; i < N; ++i) {
Transpose2D<TIndex, TData>(H, W, X + i * H * W, Y + i * H * W);
}
return;
}
TransposeND<TIndex, TData>(ndim, dims, axes, X, Y);
}
#ifdef CAFFE2_USE_HPTT
#define CAFFE2_SPECIALIZED_TRANSPOSE_IMPL(TIndex, TData) \
template <> \
void TransposeImpl<TIndex, TData>( \
const int ndim, \
const TIndex* dims, \
const int* axes, \
const TData* X, \
TData* T) { \
const TIndex size = std::accumulate( \
dims, dims + ndim, TIndex(1), std::multiplies<TIndex>()); \
if (size == 0) { \
return; \
} \
if (utils::IsIdentityPermutation(ndim, axes)) { \
std::memcpy(Y, X, size * sizeof(TData)); \
return; \
} \
if (TransposeByHPTT(ndim, dims, axes, X, Y)) { \
return; \
} \
if (utils::IsBatchTranspose2D(ndim, axes)) { \
const TIndex H = dims[ndim - 2]; \
const TIndex W = dims[ndim - 1]; \
const TIndex N = size / (H * W); \
for (TIndex i = 0; i < N; ++i) { \
Transpose2D<TIndex, TData>(H, W, X + i * H * W, Y + i * H * W); \
} \
return; \
} \
TransposeND<TIndex, TData>(ndim, dims, axes, X, Y); \
}
CAFFE2_SPECIALIZED_TRANSPOSE_IMPL(std::int32_t, float)
CAFFE2_SPECIALIZED_TRANSPOSE_IMPL(std::int64_t, float)
CAFFE2_SPECIALIZED_TRANSPOSE_IMPL(std::int32_t, double)
CAFFE2_SPECIALIZED_TRANSPOSE_IMPL(std::int64_t, double)
#undef CAFFE2_SPECIALIZED_TRANSPOSE_IMPL
#endif // CAFFE2_USE_HPTT
} // namespace
#define CAFFE2_SPECIALIZED_TRANSPOSE(TIndex, TData) \
template <> \
C10_EXPORT void Transpose<TIndex, TData, CPUContext>( \
const int ndim, \
const TIndex* dims, \
const int* axes, \
const TData* X, \
TData* Y, \
CPUContext* /* context */) { \
TransposeImpl<TIndex, TData>(ndim, dims, axes, X, Y); \
}
CAFFE2_SPECIALIZED_TRANSPOSE(std::int32_t, float)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int64_t, float)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int32_t, double)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int64_t, double)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int32_t, std::int32_t)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int64_t, std::int32_t)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int32_t, std::int64_t)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int64_t, std::int64_t)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int32_t, std::uint8_t)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int64_t, std::uint8_t)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int32_t, std::uint16_t)
CAFFE2_SPECIALIZED_TRANSPOSE(std::int64_t, std::uint16_t)
#undef CAFFE2_SPECIALIZED_TRANSPOSE
#define CAFFE2_SPECIALIZED_NCHW2NHWC(T) \
template <> \
C10_EXPORT void NCHW2NHWC<T, CPUContext>( \
const int N, \
const int C, \
const int HxW, \
const T* X, \
T* Y, \
CPUContext* /* context */) { \
const int stride = C * HxW; \
for (int i = 0; i < N; ++i) { \
Transpose2D(C, HxW, X + i * stride, Y + i * stride); \
} \
}
CAFFE2_SPECIALIZED_NCHW2NHWC(float)
#undef CAFFE2_SPECIALIZED_NCHW2NHWC
#define CAFFE2_SPECIALIZED_NHWC2NCHW(T) \
template <> \
C10_EXPORT void NHWC2NCHW<T, CPUContext>( \
const int N, \
const int C, \
const int HxW, \
const T* X, \
T* Y, \
CPUContext* /* context */) { \
const int stride = HxW * C; \
for (int i = 0; i < N; ++i) { \
Transpose2D(HxW, C, X + i * stride, Y + i * stride); \
} \
}
CAFFE2_SPECIALIZED_NHWC2NCHW(float)
#undef CAFFE2_SPECIALIZED_NHWC2NCHW
} // namespace math
} // namespace caffe2
|
