#include "softmax_layer.h" #include "blas.h" #include "cuda.h" #include #include #include #include #include softmax_layer make_softmax_layer(int batch, int inputs, int groups) { assert(inputs%groups == 0); fprintf(stderr, "Softmax Layer: %d inputs\n", inputs); softmax_layer l = {0}; l.type = SOFTMAX; l.batch = batch; l.groups = groups; l.inputs = inputs; l.outputs = inputs; l.output = calloc(inputs*batch, sizeof(float)); l.delta = calloc(inputs*batch, sizeof(float)); #ifdef GPU l.output_gpu = cuda_make_array(l.output, inputs*batch); l.delta_gpu = cuda_make_array(l.delta, inputs*batch); #endif return l; } void softmax_array(float *input, int n, float *output) { int i; float sum = 0; float largest = -FLT_MAX; for(i = 0; i < n; ++i){ if(input[i] > largest) largest = input[i]; } for(i = 0; i < n; ++i){ sum += exp(input[i]-largest); } if(sum) sum = largest+log(sum); else sum = largest-100; for(i = 0; i < n; ++i){ output[i] = exp(input[i]-sum); } } void forward_softmax_layer(const softmax_layer l, network_state state) { int b; int inputs = l.inputs / l.groups; int batch = l.batch * l.groups; for(b = 0; b < batch; ++b){ softmax_array(state.input+b*inputs, inputs, l.output+b*inputs); } } void backward_softmax_layer(const softmax_layer l, network_state state) { int i; for(i = 0; i < l.inputs*l.batch; ++i){ state.delta[i] = l.delta[i]; } }