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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/SpatialLinear.c"
#else
static int nn_(SpatialLinear_updateOutput)(lua_State *L)
{
// get all params
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
// dims
int ichannels = input->size[0];
int ochannels = output->size[0];
// planes
THTensor *outputPlane = THTensor_(new)();
THTensor *inputPlane = THTensor_(new)();
// process each plane
int ok,ik;
for (ok=0; ok<ochannels; ok++) {
// fill output
THTensor_(select)(outputPlane, output, 0, ok);
THTensor_(fill)(outputPlane, THTensor_(get1d)(bias,ok));
for (ik=0; ik<ichannels; ik++) {
// get input plane
THTensor_(select)(inputPlane, input, 0, ik);
THTensor_(cadd)(outputPlane, outputPlane, THTensor_(get2d)(weight,ok,ik), inputPlane);
}
}
// cleanup
THTensor_(free)(inputPlane);
THTensor_(free)(outputPlane);
return 1;
}
static int nn_(SpatialLinear_updateGradInput)(lua_State *L)
{
// get all params
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
int weightDecay = luaT_getfieldcheckint(L, 1, "weightDecay");
// dims
int owidth = gradOutput->size[2];
int oheight = gradOutput->size[1];
// resize gradInput
THTensor_(zero)(gradInput);
// select planes
THTensor *gradOutput_xy = THTensor_(new)();
THTensor *gradOutput_y = THTensor_(new)();
THTensor *gradInput_xy = THTensor_(new)();
THTensor *gradInput_y = THTensor_(new)();
THTensor *input_xy = THTensor_(new)();
THTensor *input_y = THTensor_(new)();
// transpose weight
THTensor *weight_t = THTensor_(newTranspose)(weight,0,1);
// compute gradient
int x,y;
for (y=0; y<oheight; y++) {
// select rows
THTensor_(select)(gradOutput_y, gradOutput, 1, y);
THTensor_(select)(gradInput_y, gradInput, 1, y);
THTensor_(select)(input_y, input, 1, y);
for (x=0; x<owidth; x++) {
// (select) cols
THTensor_(select)(gradOutput_xy, gradOutput_y, 1, x);
THTensor_(select)(gradInput_xy, gradInput_y, 1, x);
THTensor_(select)(input_xy, input_y, 1, x);
// compute dE/dW and dE/dB
THTensor_(addr)(gradWeight, 1, gradWeight, 1, gradOutput_xy, input_xy);
THTensor_(cadd)(gradBias, gradBias, 1, gradOutput_xy);
// weight decay
if (weightDecay != 0) {
THTensor_(cadd)(gradWeight, gradWeight, 1, weight);
}
// compute dE/dI
THTensor_(addmv)(gradInput_xy, 1, gradInput_xy, 1, weight_t, gradOutput_xy);
}
}
// cleanup
THTensor_(free)(gradInput_xy);
THTensor_(free)(gradInput_y);
THTensor_(free)(gradOutput_xy);
THTensor_(free)(gradOutput_y);
THTensor_(free)(input_xy);
THTensor_(free)(input_y);
THTensor_(free)(weight_t);
return 1;
}
static const struct luaL_Reg nn_(SpatialLinear__) [] = {
{"SpatialLinear_updateOutput", nn_(SpatialLinear_updateOutput)},
{"SpatialLinear_updateGradInput", nn_(SpatialLinear_updateGradInput)},
{NULL, NULL}
};
static void nn_(SpatialLinear_init)(lua_State *L)
{
luaT_pushmetatable(L, torch_Tensor);
luaT_registeratname(L, nn_(SpatialLinear__), "nn");
lua_pop(L,1);
}
#endif
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