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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/AbsCriterion.c"
#else
static int nn_(AbsCriterion_updateOutput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
THTensor *target = luaT_checkudata(L, 3, torch_(Tensor_id));
int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
real sum;
sum = 0;
TH_TENSOR_APPLY2(real, input, real, target,
sum += fabs(*input_data - *target_data);)
if(sizeAverage)
sum /= THTensor_(nElement)(input);
lua_pushnumber(L, sum);
lua_setfield(L, 1, "output");
lua_pushnumber(L, sum);
return 1;
}
static int nn_(AbsCriterion_updateGradInput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
THTensor *target = luaT_checkudata(L, 3, torch_(Tensor_id));
int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
real norm = (sizeAverage ? 1./((real)THTensor_(nElement)(input)) : 1.);
THTensor_(resizeAs)(gradInput, input);
TH_TENSOR_APPLY3(real, gradInput, real, input, real, target,
*gradInput_data = ( (*input_data - *target_data) >= 0 ? norm : -norm);)
return 1;
}
static const struct luaL_Reg nn_(AbsCriterion__) [] = {
{"AbsCriterion_updateOutput", nn_(AbsCriterion_updateOutput)},
{"AbsCriterion_updateGradInput", nn_(AbsCriterion_updateGradInput)},
{NULL, NULL}
};
static void nn_(AbsCriterion_init)(lua_State *L)
{
luaT_pushmetaclass(L, torch_(Tensor_id));
luaT_registeratname(L, nn_(AbsCriterion__), "nn");
lua_pop(L,1);
}
#endif
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