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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/SpatialDownSampling.c"
#else
static int nn_(SpatialDownSampling_updateOutput)(lua_State *L) {
// get all params
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
int rW = luaT_getfieldcheckint(L, 1, "rW");
int rH = luaT_getfieldcheckint(L, 1, "rH");
THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
// dims
int iwidth = input->size[2];
int iheight = input->size[1];
int ichannels = input->size[0];
int owidth = floor(iwidth / rW);
int oheight = floor(iheight / rH);
// get strides
long *is = input->stride;
long *os = output->stride;
// get raw pointers
real *input_data = THTensor_(data)(input);
real *output_data = THTensor_(data)(output);
// resample each plane
real avg;
real *input_p = input_data, *output_p = output_data;
int k, x, y, i, j;
for (k = 0; k < ichannels; ++k, input_p += is[0], output_p += os[0])
for (y = 0; y < oheight; ++y)
for (x = 0; x < owidth; ++x) {
avg = 0.0;
for (i = y*rH; i < (y+1)*rH; ++i)
for (j = x*rW; j < (x+1)*rW; ++j)
avg += input_p[i*is[1]+j*is[2]];
output_p[y*os[1] + x*os[2]] = avg;
}
THTensor_(mul)(output, output, 1.0f/(rH*rW));
return 1;
}
static int nn_(SpatialDownSampling_updateGradInput)(lua_State *L) {
// get all params
THTensor *gradOutput = luaT_checkudata(L, 2, torch_Tensor);
THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
int rW = luaT_getfieldcheckint(L, 1, "rW");
int rH = luaT_getfieldcheckint(L, 1, "rH");
THArgCheck(gradOutput->nDimension == 3, 2, "gradOutput must be 3D Tensor");
// dims
int owidth = gradOutput->size[2];
int oheight = gradOutput->size[1];
int ochannels = gradOutput->size[0];
// get strides
long *gis = gradInput->stride;
long *gos = gradOutput->stride;
THTensor_(zero)(gradInput);
// get raw pointers
real *gradInput_data = THTensor_(data)(gradInput);
real *gradOutput_data = THTensor_(data)(gradOutput);
// compute gradients for each plane
real *gradInput_p = gradInput_data, *gradOutput_p = gradOutput_data;
int k, x, y, i, j;
for (k = 0; k < ochannels; ++k, gradInput_p += gis[0], gradOutput_p += gos[0])
for (y = 0; y < oheight; ++y)
for (x = 0; x < owidth; ++x)
for (i = y*rH; i < (y+1)*rH; ++i)
for (j = x*rW; j < (x+1)*rW; ++j)
gradInput_p[i*gis[1]+j*gis[2]] += gradOutput_p[y*gos[1]+x*gos[2]];
THTensor_(mul)(gradInput, gradInput, 1.0f/(rH*rW));
return 1;
}
static const struct luaL_Reg nn_(SpatialDownSampling__) [] = {
{"SpatialDownSampling_updateOutput", nn_(SpatialDownSampling_updateOutput)},
{"SpatialDownSampling_updateGradInput", nn_(SpatialDownSampling_updateGradInput)},
{NULL, NULL}
};
static void nn_(SpatialDownSampling_init)(lua_State *L)
{
luaT_pushmetatable(L, torch_Tensor);
luaT_registeratname(L, nn_(SpatialDownSampling__), "nn");
lua_pop(L,1);
}
#endif
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