diff options
Diffstat (limited to 'generic/MultiMarginCriterion.c')
-rw-r--r-- | generic/MultiMarginCriterion.c | 162 |
1 files changed, 162 insertions, 0 deletions
diff --git a/generic/MultiMarginCriterion.c b/generic/MultiMarginCriterion.c new file mode 100644 index 0000000..ca73bc9 --- /dev/null +++ b/generic/MultiMarginCriterion.c @@ -0,0 +1,162 @@ +#ifndef TH_GENERIC_FILE +#define TH_GENERIC_FILE "generic/MultiMarginCriterion.c" +#else + +static int nn_(MultiMarginCriterion_updateOutput)(lua_State *L) +{ + THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id)); + int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage"); + real *input_data, *target_data; + long nframe, dim; + long t, d; + real target_; + THTensor *target; + real sum; + + THArgCheck((input->nDimension == 1) || (input->nDimension == 2), 2, "vector or matrix expected"); + + if(input->nDimension == 1) + { + nframe = 1; + dim = input->size[0]; + target_ = luaL_checknumber(L, 3); + target = THTensor_(newWithSize1d)(1); + THTensor_(fill)(target, target_); + } + else + { + nframe = input->size[0]; + dim = input->size[1]; + target = luaT_checkudata(L, 3, torch_(Tensor_id)); + THArgCheck((target->nDimension == 1) && (target->size[0] == nframe), 3, "inconsistent target size"); + target = THTensor_(newContiguous)(target); + } + + for(t = 0; t < nframe; t++) + { + real idx = THTensor_(get1d)(target, t); + THArgCheck((idx >= 1) && (idx <= dim), 3, "target out of range"); + } + + input = THTensor_(newContiguous)(input); + input_data = THTensor_(data)(input); + target_data = THTensor_(data)(target); + + sum = 0; + for(t = 0; t < nframe; t++) + { + long target_idx = (long)(target_data[t]-1); + real input_target = input_data[target_idx]; + for(d = 0; d < dim; d++) + { + real z = 1 - input_target + input_data[d]; + if(d == target_idx) + continue; + + if(z > 0) + sum += z; + } + input_data += dim; + } + + if(sizeAverage) + sum /= dim; + + lua_pushnumber(L, sum); + lua_setfield(L, 1, "output"); + + THTensor_(free)(input); + THTensor_(free)(target); + lua_pushnumber(L, sum); + return 1; +} + +static int nn_(MultiMarginCriterion_updateGradInput)(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 *input_data; + real *gradInput_data; + real *target_data; + THTensor *target; + long nframe, dim; + long t, d; + real target_; + real g; + real sum; + + THArgCheck((input->nDimension == 1) || (input->nDimension == 2), 2, "vector or matrix expected"); + + if(input->nDimension == 1) + { + nframe = 1; + dim = input->size[0]; + target_ = luaL_checknumber(L, 3); + target = THTensor_(newWithSize1d)(1); + THTensor_(fill)(target, target_); + } + else + { + nframe = input->size[0]; + dim = input->size[1]; + target = luaT_checkudata(L, 3, torch_(Tensor_id)); + THArgCheck((target->nDimension == 1) && (target->size[0] == nframe), 3, "inconsistent target size"); + target = THTensor_(newContiguous)(target); + } + + g = (sizeAverage ? 1./((real)dim) : 1.); + + input = THTensor_(newContiguous)(input); + input_data = THTensor_(data)(input); + + THTensor_(resizeAs)(gradInput, input); + gradInput_data = THTensor_(data)(gradInput); + + target_data = THTensor_(data)(target); + + for(t = 0; t < nframe; t++) + { + long target_idx = (long)(target_data[t])-1; + real input_target = input_data[target_idx]; + real gradInput_target = 0; + for(d = 0; d < dim; d++) + { + real z = 1 - input_target + input_data[d]; + if(d == target_idx) + continue; + + if(z > 0) + { + gradInput_target -= g; + gradInput_data[d] = g; + } + else + gradInput_data[d] = 0; + } + gradInput_data[target_idx] = gradInput_target; + + input_data += dim; + gradInput_data += dim; + } + + + THTensor_(free)(input); + THTensor_(free)(target); + return 1; +} + +static const struct luaL_Reg nn_(MultiMarginCriterion__) [] = { + {"MultiMarginCriterion_updateOutput", nn_(MultiMarginCriterion_updateOutput)}, + {"MultiMarginCriterion_updateGradInput", nn_(MultiMarginCriterion_updateGradInput)}, + {NULL, NULL} +}; + +static void nn_(MultiMarginCriterion_init)(lua_State *L) +{ + luaT_pushmetaclass(L, torch_(Tensor_id)); + luaT_registeratname(L, nn_(MultiMarginCriterion__), "nn"); + lua_pop(L,1); +} + +#endif |