| #ifndef TH_GENERIC_FILE |
| #define TH_GENERIC_FILE "generic/SoftMarginCriterion.c" |
| #else |
| |
| void THNN_(SoftMarginCriterion_updateOutput)( |
| THNNState *state, |
| THTensor *input, |
| THTensor *target, |
| THTensor *output, |
| bool sizeAverage) |
| { |
| THNN_CHECK_NELEMENT(input, target); |
| THNN_CHECK_DIM_SIZE(output, 1, 0, 1); |
| |
| real sum; |
| |
| sum = 0; |
| TH_TENSOR_APPLY2(real, input, real, target, |
| real z = log(1. + exp(-*input_data* *target_data)); |
| sum += z;) |
| |
| if(sizeAverage) |
| sum /= THTensor_(nElement)(input); |
| |
| THTensor_(set1d)(output, 0, sum); |
| } |
| |
| void THNN_(SoftMarginCriterion_updateGradInput)( |
| THNNState *state, |
| THTensor *input, |
| THTensor *target, |
| THTensor *gradInput, |
| bool sizeAverage) |
| { |
| THNN_CHECK_NELEMENT(input, target); |
| real norm = (sizeAverage ? 1./((real)THTensor_(nElement)(input)) : 1.); |
| |
| THTensor_(resizeAs)(gradInput, input); |
| TH_TENSOR_APPLY3(real, gradInput, real, input, real, target, |
| real z = exp(-*target_data * *input_data); |
| *gradInput_data = -norm*(*target_data)*z/(1. + z);) |
| } |
| |
| #endif |