#ifndef TH_TENSOR_APPLY_INC
#define TH_TENSOR_APPLY_INC
#include <ATen/Parallel.h>
/*
* The basic strategy for apply is as follows:
*
* 1. Starting with the outermost index, loop until we reach a dimension where the
* data is no longer contiguous, i.e. the stride at that dimension is not equal to
* the size of the tensor defined by the outer dimensions. Let's call this outer
* (contiguous) tensor A. Note that if the Tensor is contiguous, then A is equal
* to the entire Tensor. Let's call the inner tensor B.
*
* 2. We loop through the indices in B, starting at its outermost dimension. For
* example, if B is a 2x2 matrix, then we do:
*
* B[0][0]
* B[0][1]
* B[1][0]
* B[1][1]
*
* We set the offset into the underlying storage as (storageOffset + stride_B * index_B),
* i.e. basically we compute the offset into the storage as we would normally for a
* Tensor. But because we are guaranteed the subsequent data is contiguous in memory, we
* can simply loop for sizeof(A) iterations and perform the operation, without having to
* follow the order described by the strides of A.
*
* 3. As an optimization, we merge dimensions of A that are contiguous in memory. For
* example, if A is a 3x3x3x3 tensor narrowed from a 3x3x4x3 tensor, then the first two
* dimensions can be merged for the purposes of APPLY, reducing the number of nested
* loops.
*/
#define __TH_TENSOR_APPLYX_PREAMBLE(TYPE, TENSOR, DIM, ALLOW_CONTIGUOUS) \
TYPE *TENSOR##_data = NULL; \
int64_t *TENSOR##_counter = NULL, *TENSOR##_sizes = NULL, *TENSOR##_strides = NULL, *TENSOR##_dimOffset = NULL; \
int64_t TENSOR##_stride = 0, TENSOR##_size = 0, TENSOR##_dim = 0, TENSOR##_i, TENSOR##_n; \
int TENSOR##_contiguous = ALLOW_CONTIGUOUS && DIM < 0; \
TENSOR##_n = 1; \
for(TENSOR##_i = 0; TENSOR##_i < TENSOR->dim(); TENSOR##_i++) \
TENSOR##_n *= TENSOR->size(TENSOR##_i); \
\
if(TENSOR->is_empty()) \
TH_TENSOR_APPLY_hasFinished = 1; \
else \
{ \
TENSOR##_data = THTensor_getStoragePtr(TENSOR)->data<TYPE>()+TENSOR->storage_offset(); \
TENSOR##_size = 1; \
TENSOR##_stride = 1; \
for(TENSOR##_i = THTensor_nDimensionLegacyAll(TENSOR)-1; TENSOR##_i >= 0; TENSOR##_i--) { \
if(THTensor_sizeLegacyNoScalars(TENSOR, TENSOR##_i) != 1) { \
if(THTensor_strideLegacyNoScalars(TENSOR, TENSOR##_i) == TENSOR##_size && TENSOR##_i != DIM) \
TENSOR##_size *= THTensor_sizeLegacyNoScalars(TENSOR, TENSOR##_i); \
else{ \
TENSOR##_contiguous = 0; \
break; \
} \
} \
} \
if (!TENSOR##_contiguous) { \
/* Find the dimension of contiguous sections */ \
TENSOR##_dim = 1; \
for(TENSOR##_i = THTensor_nDimensionLegacyAll(TENSOR)-2; TENSOR##_i >= 0; TENSOR##_i--) \
{ \
if(TENSOR->stride(TENSOR##_i) != TENSOR->stride(TENSOR##_i+1) * TENSOR->size(TENSOR##_i+1) || TENSOR##_i == DIM || TENSOR##_i+1 == DIM) \
TENSOR##_dim++; \
} \
/* Allocate an array of 3*dim elements, where dim is the number of contiguous sections */ \
TENSOR##_counter = (int64_t*)THAlloc(sizeof(int64_t)*(3*TENSOR##_dim)); \
TENSOR##_sizes = TENSOR##_counter + TENSOR##_dim; \
TENSOR##_strides = TENSOR##_counter + 2*TENSOR##_dim; \
TH_TENSOR_dim_index = TENSOR##_dim-1; \
TENSOR##_dimOffset = (DIM == THTensor_nDimensionLegacyAll(TENSOR)-1) ? &TENSOR##_i : &TENSOR##_counter[DIM]; \
TENSOR##_sizes[TH_TENSOR_dim_index] = THTensor_sizeLegacyNoScalars(TENSOR, THTensor_nDimensionLegacyAll(TENSOR)-1); \
TENSOR##_strides[TH_TENSOR_dim_index] = THTensor_strideLegacyNoScalars(TENSOR, THTensor_nDimensionLegacyAll(TENSOR)-1); \
/* TENSOR##_counter tracks where we are in the storage. The offset into the */ \
/* storage is given by storage_offset + (i * j), where i is the stride */ \
/* vector and j is tensor_counter vector. This sets the starting position for the loop. */ \
for(TENSOR##_i = TENSOR##_dim-1; TENSOR##_i >= 0; --TENSOR##_i) { \
TENSOR##_counter[TENSOR##_i] = 0; \
} \
for(TENSOR##_i = THTensor_nDimensionLegacyAll(TENSOR)-2; TENSOR##_i >= 0; --TENSOR##_i) { \
if (TENSOR->stride(TENSOR##_i) == TENSOR->stride(TENSOR##_i+1) * TENSOR->size(TENSOR##_i+1) && TENSOR##_i != DIM && TENSOR##_i+1 != DIM) { \
TENSOR##_sizes[TH_TENSOR_dim_index] = TENSOR->size(TENSOR##_i) * TENSOR##_sizes[TH_TENSOR_dim_index]; \
if (DIM != THTensor_nDimensionLegacyAll(TENSOR)-1 && TENSOR##_i < DIM) \
TENSOR##_dimOffset--; \
} else { \
--TH_TENSOR_dim_index; \
TENSOR##_sizes[TH_TENSOR_dim_index] = TENSOR->size(TENSOR##_i); \
TENSOR##_strides[TH_TENSOR_dim_index] = TENSOR->stride(TENSOR##_i); \
} \
} \
/* Size of the inner most section */ \
TENSOR##_size = TENSOR##_sizes[TENSOR##_dim-1]; \
/* Stride of the inner most section */ \
TENSOR##_stride = TENSOR##_strides[TENSOR##_dim-1]; \
} \
else{\
TENSOR##_dim = 1;\
TENSOR##_counter = (int64_t*)THAlloc(sizeof(int64_t)*3);\
TENSOR##_sizes = TENSOR##_counter + 1;\
TENSOR##_strides = TENSOR##_counter + 2;\
TENSOR##_sizes[0] = TENSOR##_n;\
TENSOR##_strides[0] = 1;\
TENSOR##_size = TENSOR##_sizes[0];\
TENSOR##_stride = TENSOR##_strides[0];\
}\
} \
TENSOR##_i = 0;
#define __TH_TENSOR_APPLYX_UPDATE_COUNTERS(TENSOR, ALWAYS_UPDATE) \
if(TENSOR##_i == TENSOR##_size || ALWAYS_UPDATE) \
{ \
if(TENSOR##_contiguous) \
break; \
\
if(TENSOR##_dim == 1) \
break; \
\
/* Reset pointer to beginning of loop */ \
TENSOR##_data -= TENSOR##_size*TENSOR##_stride; \
for(TENSOR##_i = TENSOR##_dim-2; TENSOR##_i >= 0; TENSOR##_i--) \
{ \
TENSOR##_counter[TENSOR##_i]++; \
/* Jump ahread by the stride of this dimension */ \
TENSOR##_data += TENSOR##_strides[TENSOR##_i]; \
\
if(TENSOR##_counter[TENSOR##_i] == TENSOR##_sizes[TENSOR##_i]) \
{ \
if(TENSOR##_i == 0) \
{ \
TH_TENSOR_APPLY_hasFinished = 1; \
break; \
} \
else \
{ \
/* Reset the pointer to the beginning of the chunk defined by this dimension */ \
TENSOR##_data -= TENSOR##_counter[TENSOR##_i]*TENSOR##_strides[TENSOR##_i]; \
TENSOR##_counter[TENSOR##_i] = 0; \
} \
} \
else \
break; \
} \
TENSOR##_i = 0; \
} \
#define TH_TENSOR_APPLY3_D(TYPE1, TENSOR1, TYPE2, TENSOR2, TYPE3, TENSOR3, DIM, CODE) \
{ \
int TH_TENSOR_APPLY_hasFinished = 0; \
int64_t TH_TENSOR_dim_index = 0; \
__TH_TENSOR_APPLYX_PREAMBLE(TYPE1, TENSOR1, DIM, 1) \
__TH_TENSOR_APPLYX_PREAMBLE(TYPE2, TENSOR2, DIM, 1) \
__TH_TENSOR_APPLYX_PREAMBLE(TYPE3, TENSOR3, DIM, 1) \
\
int elements_equal = 1; \
if(TENSOR1##_n != TENSOR2##_n) { \
elements_equal = 0; \
} \
else if(TENSOR1##_n != TENSOR3##_n) { \
elements_equal = 0; \
} \
if (elements_equal == 0) { \
AT_ERROR("inconsistent tensor size, expected ", \
#TENSOR1, " ", TENSOR1->sizes(), ", ", \
#TENSOR2, " ", TENSOR2->sizes(), " and ", \
#TENSOR3, " ", TENSOR3->sizes(), " to have the same " \
"number of elements, but got ", TENSOR1##_n, ", ", \
TENSOR2##_n, " and ", TENSOR3##_n, " elements respectively"); \
} \
\
while(!TH_TENSOR_APPLY_hasFinished) \
{ \
/* Loop through the inner most region of the Tensor */ \
for(; TENSOR1##_i < TENSOR1##_size && TENSOR2##_i < TENSOR2##_size && TENSOR3##_i < TENSOR3##_size; TENSOR1##_i++, TENSOR2##_i++, TENSOR3##_i++, TENSOR1##_data += TENSOR1##_stride, TENSOR2##_data += TENSOR2##_stride, TENSOR3##_data += TENSOR3##_stride) /* 0 et pas TENSOR##_dim! */ \
{ \
CODE \
} \
__TH_TENSOR_APPLYX_UPDATE_COUNTERS(TENSOR1, 0) \
__TH_TENSOR_APPLYX_UPDATE_COUNTERS(TENSOR2, 0) \
__TH_TENSOR_APPLYX_UPDATE_COUNTERS(TENSOR3, 0) \
} \
if(TENSOR1##_counter != NULL) \
THFree(TENSOR1##_counter); \
if(TENSOR2##_counter != NULL) \
THFree(TENSOR2##_counter); \
if(TENSOR3##_counter != NULL) \
THFree(TENSOR3##_counter); \
}
#define TH_TENSOR_APPLY3(TYPE1, TENSOR1, TYPE2, TENSOR2, TYPE3, TENSOR3, CODE) \
TH_TENSOR_APPLY3_D(TYPE1, TENSOR1, TYPE2, TENSOR2, TYPE3, TENSOR3, -1, CODE)
#define TH_TENSOR_APPLY2_D(TYPE1, TENSOR1, TYPE2, TENSOR2, DIM, CODE) \
{ \
int TH_TENSOR_APPLY_hasFinished = 0; \
int64_t TH_TENSOR_dim_index = 0; \
__TH_TENSOR_APPLYX_PREAMBLE(TYPE1, TENSOR1, DIM, 1) \
__TH_TENSOR_APPLYX_PREAMBLE(TYPE2, TENSOR2, DIM, 1) \
\
if(TENSOR1##_n != TENSOR2##_n) { \
AT_ERROR("inconsistent tensor size, expected ", \
#TENSOR1, " ", TENSOR1->sizes(), " and ", \
#TENSOR2, " ", TENSOR2->sizes(), \
" to have the same number of elements, but got ", \
TENSOR1##_n, " and ", TENSOR2##_n, " elements respectively"); \
} \
while(!TH_TENSOR_APPLY_hasFinished) \
{ \
/* Loop through the inner most region of the Tensor */ \
for(; TENSOR1##_i < TENSOR1##_size && TENSOR2##_i < TENSOR2##_size; TENSOR1##_i++, TENSOR2##_i++, TENSOR1##_data += TENSOR1##_stride, TENSOR2##_data += TENSOR2##_stride) /* 0 et pas TENSOR##_dim! */ \
{ \
CODE \
} \
__TH_TENSOR_APPLYX_UPDATE_COUNTERS(TENSOR1, 0) \
__TH_TENSOR_APPLYX_UPDATE_COUNTERS(TENSOR2, 0) \
} \
if(TENSOR1##_counter != NULL) \
THFree(TENSOR1##_counter); \
if(TENSOR2##_counter != NULL) \
THFree(TENSOR2##_counter); \
}
#define TH_TENSOR_APPLY2(TYPE1, TENSOR1, TYPE2, TENSOR2, CODE) \
TH_TENSOR_APPLY2_D(TYPE1, TENSOR1, TYPE2, TENSOR2, -1, CODE)
#define TH_TENSOR_APPLY_D(TYPE, TENSOR, DIM, CODE) \
{ \
int TH_TENSOR_APPLY_hasFinished = 0; \
int64_t TH_TENSOR_dim_index = 0; \
__TH_TENSOR_APPLYX_PREAMBLE(TYPE, TENSOR, DIM, 0) \
\
while(!TH_TENSOR_APPLY_hasFinished) \
{ \
/* Loop through the inner most region of the Tensor */ \
for(; TENSOR##_i < TENSOR##_size; TENSOR##_i++, TENSOR##_data += TENSOR##_stride) /* 0 et pas TENSOR##_dim! */ \
{ \
CODE \
} \
__TH_TENSOR_APPLYX_UPDATE_COUNTERS(TENSOR, 1) \
} \
THFree(TENSOR##_counter); \
}
#define TH_TENSOR_APPLY(TYPE, TENSOR, CODE) \
TH_TENSOR_APPLY_D(TYPE, TENSOR, -1, CODE)
/*
* Calcuate the memory offset of an element in a tensor. The strategy is below:
*
* 1. convert the line index(the index of the element) to the indexs(coordinates) in the tensor.
* It can hinted by a classical problem: Getting each individual digit from a whole integer(Decimal base).
* A N-digit decimal base number could be view as a N-dimension tensor and the sizes of the tensor are 10.
* So the value the whole integer is the line index. And the digits could be viewed as the indexes in
* different dimensions.
*
* 2. convert the indexs(coordinates) in the tensor to the memory offset.
*
* You can get the detailes in the for-statement iterations.
*
* The macro is only used in the first element in each thread. For the rest, the memory offset could update
* according to info of the tensor in order to get better performance. So we should also record the each
* indexs in coresponding dimension of first element.
* The recorded info is stored in the TENSOR##_counter_tmp.
*
*/
#define __TH_TENSOR_APPLYX_CAL_MEMORY_OFFSET(TENSOR) \
int64_t *TENSOR##_counter_tmp = (int64_t*)THAlloc(sizeof(int64_t) * TENSOR##_dim); \
ptrdiff_t TENSOR##_memory_offset = 0; \
ptrdiff_t TENSOR##_quot = line_index_start; \
for (TENSOR##_i = TENSOR##_dim-1; TENSOR##_i>=0; --TENSOR##_i) { \
TENSOR##_counter_tmp[TENSOR##_i] = TENSOR##_quot%TENSOR##_sizes[TENSOR##_i]; \
TENSOR##_quot /= TENSOR##_sizes[TENSOR##_i]; \
TENSOR##_memory_offset += TENSOR##_counter_tmp[TENSOR##_i] * TENSOR##_strides[TENSOR##_i]; \
}
/*
* The macro update the indexes in each dimension of the elements except for the first one allocated in
* each thread.
* For a tensor, if the index of some dimension reaches the size of the corresponding dimension. It will carry and clear.
* If the index of next high dimension does do, the index of next high dimension should carry and clear, too.
*
* The momery offset calculatation is a little confusing. If current index carries, the current index is set to 0. So
* the offset should decrease by size*stride of the last dimension. Then the index next high dimension increases by 1. So
* the offset should increase by stride of next high dimension.
*/
#define __TH_TENSOR_APPLYX_UPDATE_COUNTERS_PARALLEL(TENSOR) \
if(TENSOR##_i == TENSOR##_size && TENSOR##_dim > 1){ /*reaches the edge*/ \
int TENSOR##_carry_coord = 1; /*set carry flag to true*/ \
TENSOR##_start = 0; /*the current index be cleared to 0*/\
TENSOR##_data -= TENSOR##_size * TENSOR##_stride; /*the momery offset reset to the first one in current dimension */\
for(TENSOR##_i = TENSOR##_dim - 2; (TENSOR##_i >= 0) && (TENSOR##_carry_coord); TENSOR##_i--){ \
TENSOR##_counter_tmp[TENSOR##_i]++; /*the index of next high dimension update*/ \
TENSOR##_data += TENSOR##_strides[TENSOR##_i]; /*memory offset increase by stride of next high dimension*/\
if(TENSOR##_counter_tmp[TENSOR##_i] == TENSOR##_sizes[TENSOR##_i]){ /*The next high dimension also carry, continue
to clear and carry*/ \
TENSOR##_data -= TENSOR##_sizes[TENSOR##_i] * TENSOR##_strides[TENSOR##_i]; \
TENSOR##_counter_tmp[TENSOR##_i] = 0; \
} else { \
TENSOR##_carry_coord = 0; \
} \
} \
} else { \
TENSOR##_start = TENSOR##_i; \
}
#endif