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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/SpatialRadialMatching.c"
#else
#define square(x) ((x)*(x))
#define max(x,y) (((x)>(y)) ? (x) : (y))
#define min(x,y) (((x)>(y)) ? (y) : (x))
static int nn_(SpatialRadialMatching_updateOutput)(lua_State *L)
{
// get all params
THTensor *input1 = luaT_checkudata(L, 2, torch_Tensor);
THTensor *input2 = luaT_checkudata(L, 3, torch_Tensor);
//THLongTensor *mask= luaT_checkudata(L, 4, luaT_checktypename2id(L, "torch.LongTensor"));
int maxh = luaT_getfieldcheckint(L, 1, "maxh");
THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
// dims
int iwidth = input1->size[2];
int iheight = input1->size[1];
int ichannels = input1->size[0];
// get strides
long *i1s = input1->stride;
long *i2s = input2->stride;
//long *ms = mask ->stride;
long *os = output->stride;
// get pointers
real *input1_p = THTensor_(data)(input1);
real *input2_p = THTensor_(data)(input2);
//long *mask_p = THLongTensor_data(mask);
real *output_p = THTensor_(data)(output);
// compute output
int x1,y1,y2,k;
real dist;
#pragma omp parallel for private(y1,x1,y2,k,dist)
for (y1 = 0; y1 < iheight; y1++) {
for (x1 = 0; x1 < iwidth; x1++) {
//if (mask_p[y1*ms[0] + x1*ms[1]]) {
for (y2 = y1; y2 < y1+maxh; y2++) {
dist = 0.0f;
for (k = 0; k < ichannels; k++)
dist += square( input1_p[k*i1s[0] + y1*i1s[1] + x1*i1s[2]]
- input2_p[k*i2s[0] + y2*i2s[1] + x1*i2s[2]]);
output_p[(y2-y1)*os[2] + y1*os[0] + x1*os[1]] = dist;
}
//}
}
}
// done
return 0;
}
static int nn_(SpatialRadialMatching_updateGradInput)(lua_State *L)
{
// get all params
THTensor* input1 = luaT_checkudata(L, 2, torch_Tensor);
THTensor* input2 = luaT_checkudata(L, 3, torch_Tensor);
THTensor* gradOutput = luaT_checkudata(L, 4, torch_Tensor);
//THLongTensor* mask = luaT_checkudata(L, 5, luaT_checktypename2id(L, "torch.LongTensor"));
THTensor* gradInput1 = luaT_getfieldcheckudata(L, 1, "gradInput1", torch_Tensor);
THTensor* gradInput2 = luaT_getfieldcheckudata(L, 1, "gradInput2", torch_Tensor);
int maxh = luaT_getfieldcheckint(L, 1, "maxh");
// dims
int iwidth = input1->size[2];
int iheight = input1->size[1];
int ichannels = input1->size[0];
// get strides
long* i1s = input1->stride;
long* i2s = input2->stride;
long* gi1s = gradInput1->stride;
long* gi2s = gradInput2->stride;
long* gos = gradOutput->stride;
//long* ms = mask->stride;
// get pointers
real* input1_p = THTensor_(data)(input1);
real* input2_p = THTensor_(data)(input2);
real* gradInput1_p = THTensor_(data)(gradInput1);
real* gradInput2_p = THTensor_(data)(gradInput2);
real* gradOutput_p = THTensor_(data)(gradOutput);
//long* mask_p = THLongTensor_data(mask);
// compute gradients
int x1, y1, y2, k;
real partial_d;
for (y1 = 0; y1 < iheight; y1++) {
for (x1 = 0; x1 < iwidth; x1++) {
// if (mask_p[y1*ms[0] + x1*ms[1]]) {
for (y2 = y1; y2 < y1+maxh; y2++) {
for (k = 0; k < ichannels; k++) {
partial_d = 2.0f*( input1_p[k*i1s[0] + y1*i1s[1] + x1*i1s[2]]
- input2_p[k*i2s[0] + y2*i2s[1] + x1*i2s[2]]);
partial_d *= gradOutput_p[(y2-y1)*gos[2]+y1*gos[0]+x1*gos[1]];
gradInput1_p[k*gi1s[0] + y1*gi1s[1] + x1*gi1s[2]] += partial_d;
gradInput2_p[k*gi2s[0] + y2*gi2s[1] + x1*gi2s[2]] -= partial_d;
}
}
//}
}
}
// done
return 0;
}
static const struct luaL_Reg nn_(SpatialRadialMatching__) [] = {
{"SpatialRadialMatching_updateOutput", nn_(SpatialRadialMatching_updateOutput)},
{"SpatialRadialMatching_updateGradInput", nn_(SpatialRadialMatching_updateGradInput)},
{NULL, NULL}
};
static void nn_(SpatialRadialMatching_init)(lua_State *L)
{
luaT_pushmetatable(L, torch_Tensor);
luaT_registeratname(L, nn_(SpatialRadialMatching__), "nn");
lua_pop(L,1);
}
#endif
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