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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/SparseCriterion.c"
#else
static int nn_(SparseCriterion_forward)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
real sum = 0;
TH_TENSOR_APPLY(real, input, sum += fabs(*input_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_(SparseCriterion_backward)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, 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_APPLY2(real, gradInput, real, input,
*gradInput_data = ( *input_data >= 0 ? norm : -norm);)
return 1;
}
static const struct luaL_Reg nn_(SparseCriterion__) [] = {
{"SparseCriterion_forward", nn_(SparseCriterion_forward)},
{"SparseCriterion_backward", nn_(SparseCriterion_backward)},
{NULL, NULL}
};
static void nn_(SparseCriterion_init)(lua_State *L)
{
luaT_pushmetaclass(L, torch_(Tensor_id));
luaT_registeratname(L, nn_(SparseCriterion__), "nn");
lua_pop(L,1);
}
#endif
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