/usr/include/TH/THTensorDimApply.h is in libtorch-th-dev 0~20170926-g89ede3b-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 | #ifndef TH_TENSOR_DIM_APPLY_INC
#define TH_TENSOR_DIM_APPLY_INC
#define TH_TENSOR_DIM_APPLY3(TYPE1, TENSOR1, TYPE2, TENSOR2, TYPE3, TENSOR3, DIMENSION, CODE) \
{ \
TYPE1 *TENSOR1##_data = NULL; \
long TENSOR1##_stride = 0, TENSOR1##_size = 0; \
TYPE2 *TENSOR2##_data = NULL; \
long TENSOR2##_stride = 0, TENSOR2##_size = 0; \
TYPE3 *TENSOR3##_data = NULL; \
long TENSOR3##_stride = 0, TENSOR3##_size = 0; \
long *TH_TENSOR_DIM_APPLY_counter = NULL; \
int TH_TENSOR_DIM_APPLY_hasFinished = 0; \
int TH_TENSOR_DIM_APPLY_i; \
\
if( (DIMENSION < 0) || (DIMENSION >= TENSOR1->nDimension) ) \
THError("invalid dimension %d (expected to be 0 <= dim < %d)", DIMENSION, TENSOR1->nDimension); \
int same_dims = 1; \
if( TENSOR1->nDimension != TENSOR2->nDimension ) { \
same_dims = 0; \
} \
if( TENSOR1->nDimension != TENSOR3->nDimension ) { \
same_dims = 0; \
} \
if (same_dims == 0) { \
THDescBuff T1buff = _THSizeDesc(TENSOR1->size, TENSOR1->nDimension); \
THDescBuff T2buff = _THSizeDesc(TENSOR2->size, TENSOR2->nDimension); \
THDescBuff T3buff = _THSizeDesc(TENSOR3->size, TENSOR3->nDimension); \
THError("inconsistent tensor size, expected %s %s, %s %s and %s %s to have the same " \
"number of dimensions", #TENSOR1, T1buff.str, #TENSOR2, T2buff.str, #TENSOR3, T3buff.str); \
} \
int shape_check_flag = 0; \
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR1->nDimension; TH_TENSOR_DIM_APPLY_i++) \
{ \
if(TH_TENSOR_DIM_APPLY_i == DIMENSION) \
continue; \
if(TENSOR1->size[TH_TENSOR_DIM_APPLY_i] != TENSOR2->size[TH_TENSOR_DIM_APPLY_i]) \
shape_check_flag = 1; \
if(TENSOR1->size[TH_TENSOR_DIM_APPLY_i] != TENSOR3->size[TH_TENSOR_DIM_APPLY_i]) \
shape_check_flag = 1; \
} \
\
if (shape_check_flag == 1) { \
THDescBuff T1buff = _THSizeDesc(TENSOR1->size, TENSOR1->nDimension); \
THDescBuff T2buff = _THSizeDesc(TENSOR2->size, TENSOR2->nDimension); \
THDescBuff T3buff = _THSizeDesc(TENSOR3->size, TENSOR3->nDimension); \
THError("Expected %s %s, %s %s and %s %s to have the same size in dimension %d", \
#TENSOR1, T1buff.str, #TENSOR2, T2buff.str, #TENSOR3, T3buff.str, DIMENSION); \
} \
\
TH_TENSOR_DIM_APPLY_counter = (long*)THAlloc(sizeof(long)*(TENSOR1->nDimension)); \
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR1->nDimension; TH_TENSOR_DIM_APPLY_i++) \
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] = 0; \
\
TENSOR1##_data = (TENSOR1)->storage->data+(TENSOR1)->storageOffset; \
TENSOR1##_stride = (TENSOR1)->stride[DIMENSION]; \
TENSOR1##_size = TENSOR1->size[DIMENSION]; \
\
TENSOR2##_data = (TENSOR2)->storage->data+(TENSOR2)->storageOffset; \
TENSOR2##_stride = (TENSOR2)->stride[DIMENSION]; \
TENSOR2##_size = TENSOR2->size[DIMENSION]; \
\
TENSOR3##_data = (TENSOR3)->storage->data+(TENSOR3)->storageOffset; \
TENSOR3##_stride = (TENSOR3)->stride[DIMENSION]; \
TENSOR3##_size = TENSOR3->size[DIMENSION]; \
\
while(!TH_TENSOR_DIM_APPLY_hasFinished) \
{ \
CODE \
\
if(TENSOR1->nDimension == 1) \
break; \
\
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR1->nDimension; TH_TENSOR_DIM_APPLY_i++) \
{ \
if(TH_TENSOR_DIM_APPLY_i == DIMENSION) \
{ \
if(TH_TENSOR_DIM_APPLY_i == TENSOR1->nDimension-1) \
{ \
TH_TENSOR_DIM_APPLY_hasFinished = 1; \
break; \
} \
continue; \
} \
\
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]++; \
TENSOR1##_data += TENSOR1->stride[TH_TENSOR_DIM_APPLY_i]; \
TENSOR2##_data += TENSOR2->stride[TH_TENSOR_DIM_APPLY_i]; \
TENSOR3##_data += TENSOR3->stride[TH_TENSOR_DIM_APPLY_i]; \
\
if(TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] == TENSOR1->size[TH_TENSOR_DIM_APPLY_i]) \
{ \
if(TH_TENSOR_DIM_APPLY_i == TENSOR1->nDimension-1) \
{ \
TH_TENSOR_DIM_APPLY_hasFinished = 1; \
break; \
} \
else \
{ \
TENSOR1##_data -= TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]*TENSOR1->stride[TH_TENSOR_DIM_APPLY_i]; \
TENSOR2##_data -= TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]*TENSOR2->stride[TH_TENSOR_DIM_APPLY_i]; \
TENSOR3##_data -= TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]*TENSOR3->stride[TH_TENSOR_DIM_APPLY_i]; \
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] = 0; \
} \
} \
else \
break; \
} \
} \
THFree(TH_TENSOR_DIM_APPLY_counter); \
}
/**
* Similar to DIM_APPLY(...) but we maintain two sets of pointers: one for the first tensor
* and one for the second. The two tensors must have the same shape, other than at the
* specified DIMENSION. This function makes it easy to store the output from reducing the
* TENSOR at index. For example, in the sum example described below, we could instead do:
*
* long i = 0;
* TYPE1 sum;
*
* for (i = 0; i < TENSOR1##_size; ++i) {
* sum += TENSOR1##_data[i * TENSOR1##_stride]
* }
* *TENSOR2##_data = (TYPE2) sum;
*
* In particular, we guarantee that the offset into TENSOR2 will be what you would get if
* you applied all of the index values used to generate the offset into TENSOR1.
*/
#define TH_TENSOR_DIM_APPLY2(TYPE1, TENSOR1, TYPE2, TENSOR2, DIMENSION, CODE) \
{ \
TYPE1 *TENSOR1##_data = NULL; \
long TENSOR1##_stride = 0, TENSOR1##_size = 0; \
TYPE2 *TENSOR2##_data = NULL; \
long TENSOR2##_stride = 0, TENSOR2##_size = 0; \
long *TH_TENSOR_DIM_APPLY_counter = NULL; \
int TH_TENSOR_DIM_APPLY_hasFinished = 0; \
int TH_TENSOR_DIM_APPLY_i; \
\
if( (DIMENSION < 0) || (DIMENSION >= TENSOR1->nDimension) ) \
THError("invalid dimension %d (expected to be 0 <= dim < %d)", DIMENSION, TENSOR1->nDimension); \
if( TENSOR1->nDimension != TENSOR2->nDimension ) { \
THDescBuff T1buff = _THSizeDesc(TENSOR1->size, TENSOR1->nDimension); \
THDescBuff T2buff = _THSizeDesc(TENSOR2->size, TENSOR2->nDimension); \
THError("inconsistent tensor size, expected %s %s and %s %s to have the same " \
"number of dimensions", #TENSOR1, T1buff.str, #TENSOR2, T2buff.str); \
} \
int shape_check_flag = 0; \
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR1->nDimension; TH_TENSOR_DIM_APPLY_i++) \
{ \
if(TH_TENSOR_DIM_APPLY_i == DIMENSION) \
continue; \
if(TENSOR1->size[TH_TENSOR_DIM_APPLY_i] != TENSOR2->size[TH_TENSOR_DIM_APPLY_i]) { \
THDescBuff T1buff = _THSizeDesc(TENSOR1->size, TENSOR1->nDimension); \
THDescBuff T2buff = _THSizeDesc(TENSOR2->size, TENSOR2->nDimension); \
THError("Expected %s %s and %s %s to have the same size in dimension %d", \
#TENSOR1, T1buff.str, #TENSOR2, T2buff.str, DIMENSION); \
} \
} \
\
TH_TENSOR_DIM_APPLY_counter = (long*)THAlloc(sizeof(long)*(TENSOR1->nDimension)); \
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR1->nDimension; TH_TENSOR_DIM_APPLY_i++) \
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] = 0; \
\
TENSOR1##_data = (TENSOR1)->storage->data+(TENSOR1)->storageOffset; \
TENSOR1##_stride = (TENSOR1)->stride[DIMENSION]; \
TENSOR1##_size = TENSOR1->size[DIMENSION]; \
\
TENSOR2##_data = (TENSOR2)->storage->data+(TENSOR2)->storageOffset; \
TENSOR2##_stride = (TENSOR2)->stride[DIMENSION]; \
TENSOR2##_size = TENSOR2->size[DIMENSION]; \
\
while(!TH_TENSOR_DIM_APPLY_hasFinished) \
{ \
CODE \
\
if(TENSOR1->nDimension == 1) \
break; \
\
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR1->nDimension; TH_TENSOR_DIM_APPLY_i++) \
{ \
if(TH_TENSOR_DIM_APPLY_i == DIMENSION) \
{ \
if(TH_TENSOR_DIM_APPLY_i == TENSOR1->nDimension-1) \
{ \
TH_TENSOR_DIM_APPLY_hasFinished = 1; \
break; \
} \
continue; \
} \
\
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]++; \
TENSOR1##_data += TENSOR1->stride[TH_TENSOR_DIM_APPLY_i]; \
TENSOR2##_data += TENSOR2->stride[TH_TENSOR_DIM_APPLY_i]; \
\
if(TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] == TENSOR1->size[TH_TENSOR_DIM_APPLY_i]) \
{ \
if(TH_TENSOR_DIM_APPLY_i == TENSOR1->nDimension-1) \
{ \
TH_TENSOR_DIM_APPLY_hasFinished = 1; \
break; \
} \
else \
{ \
TENSOR1##_data -= TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]*TENSOR1->stride[TH_TENSOR_DIM_APPLY_i]; \
TENSOR2##_data -= TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]*TENSOR2->stride[TH_TENSOR_DIM_APPLY_i]; \
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] = 0; \
} \
} \
else \
break; \
} \
} \
THFree(TH_TENSOR_DIM_APPLY_counter); \
}
/**
* The basic idea for DIM_APPLY: Given a TENSOR and a DIMENSION, provide access to the data stored
* at all sets of dimension values other than DIMENSION, such that we can get all the values at those
* fixed indices for the various values at DIMENSION.
*
* Suppose we have a 2x3x4 Tensor A, and we have DIMENSION=2. Then we will hit CODE (2x3) times, and the
* pointer into storage will be at:
*
* A[0][0]
* A[0][1]
* A[0][2]
* A[1][0]
* A[1][1]
* A[1][2]
*
* And at each point, we can access the data for each of the four elements of the Tensor via
* TENSOR##_stride. So for example, if we wanted to sum the elements there, we could do:
*
* long i = 0;
* TYPE sum;
* for (i = 0; i < TENSOR##_size; i++) {
* sum += TENSOR##_data[i * TENSOR##_stride]
* }
*
* Note that we don't have to have DIMENSION be the last tensor. If we have DIMENSION=1, then we will hit the
* code (2x4) times, with pointer into the storage at:
*
* offset +
* stride_0 * 0 + stride_2 * 0
* stride_0 * 1 + stride_2 * 0
* stride_0 * 0 + stride_2 * 1
* stride_0 * 1 + stride_2 * 1
* stride_0 * 0 + stride_2 * 2
* stride_0 * 1 + stride_2 * 2
* stride_0 * 0 + stride_2 * 3
* stride_0 * 1 + stride_2 * 3
*
* So we can again sum over the values at DIMENSION with the other indices fixed.
*/
#define TH_TENSOR_DIM_APPLY(TYPE, TENSOR, DIMENSION, CODE) \
{ \
TYPE *TENSOR##_data = NULL; \
long TENSOR##_stride = 0, TENSOR##_size = 0; \
long *TH_TENSOR_DIM_APPLY_counter = NULL; \
int TH_TENSOR_DIM_APPLY_hasFinished = 0; \
int TH_TENSOR_DIM_APPLY_i; \
\
if( (DIMENSION < 0) || (DIMENSION >= TENSOR->nDimension) ) \
THError("invalid dimension"); \
\
TENSOR##_data = (TENSOR)->storage->data+(TENSOR)->storageOffset; \
TENSOR##_stride = (TENSOR)->stride[DIMENSION]; \
TENSOR##_size = TENSOR->size[DIMENSION]; \
/* Counter stores the indices into the Tensor at any time */ \
TH_TENSOR_DIM_APPLY_counter = (long*)THAlloc(sizeof(long)*(TENSOR->nDimension)); \
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR->nDimension; TH_TENSOR_DIM_APPLY_i++) \
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] = 0; \
\
while(!TH_TENSOR_DIM_APPLY_hasFinished) \
{ \
CODE \
\
if(TENSOR->nDimension == 1) \
break; \
\
for(TH_TENSOR_DIM_APPLY_i = 0; TH_TENSOR_DIM_APPLY_i < TENSOR->nDimension; TH_TENSOR_DIM_APPLY_i++) \
{ \
/* Check if the index is equal to DIMENSION. We don't need to update the */ \
/* offset if this is the case, and can consider the next index. However, */ \
/* in the case that the DIMENSION is the last index in the Tensor, then */ \
/* we have parsed the entire tensor and can exit */ \
if(TH_TENSOR_DIM_APPLY_i == DIMENSION) \
{ \
if(TH_TENSOR_DIM_APPLY_i == TENSOR->nDimension-1) \
{ \
TH_TENSOR_DIM_APPLY_hasFinished = 1; \
break; \
} \
continue; \
} \
\
/* Bump the counter at this index, update the pointer */ \
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]++; \
TENSOR##_data += TENSOR->stride[TH_TENSOR_DIM_APPLY_i]; \
\
if(TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] == TENSOR->size[TH_TENSOR_DIM_APPLY_i]) \
{ \
/* Handled TENSOR_size(dim) iterations for DIM_APPLY_i. If this is the last dimension, exit */ \
if(TH_TENSOR_DIM_APPLY_i == TENSOR->nDimension-1) \
{ \
TH_TENSOR_DIM_APPLY_hasFinished = 1; \
break; \
} \
else \
{ \
/* Reset the counter, and the pointer to the beginning of the storage for this combination of indices */ \
TENSOR##_data -= TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i]*TENSOR->stride[TH_TENSOR_DIM_APPLY_i]; \
TH_TENSOR_DIM_APPLY_counter[TH_TENSOR_DIM_APPLY_i] = 0; \
} \
} \
else \
break; \
} \
} \
THFree(TH_TENSOR_DIM_APPLY_counter); \
}
#endif
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