#include "softmax_layer.h"
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#include "blas.h"
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#include "cuda.h"
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#include <float.h>
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#include <math.h>
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#include <stdlib.h>
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#include <stdio.h>
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#include <assert.h>
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softmax_layer *make_softmax_layer(int batch, int inputs, int groups)
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{
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assert(inputs%groups == 0);
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fprintf(stderr, "Softmax Layer: %d inputs\n", inputs);
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softmax_layer *layer = calloc(1, sizeof(softmax_layer));
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layer->batch = batch;
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layer->groups = groups;
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layer->inputs = inputs;
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layer->output = calloc(inputs*batch, sizeof(float));
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layer->delta = calloc(inputs*batch, sizeof(float));
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#ifdef GPU
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layer->output_gpu = cuda_make_array(layer->output, inputs*batch);
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layer->delta_gpu = cuda_make_array(layer->delta, inputs*batch);
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#endif
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return layer;
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}
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void softmax_array(float *input, int n, float *output)
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{
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int i;
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float sum = 0;
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float largest = -FLT_MAX;
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for(i = 0; i < n; ++i){
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if(input[i] > largest) largest = input[i];
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}
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for(i = 0; i < n; ++i){
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sum += exp(input[i]-largest);
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}
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if(sum) sum = largest+log(sum);
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else sum = largest-100;
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for(i = 0; i < n; ++i){
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output[i] = exp(input[i]-sum);
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}
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}
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void forward_softmax_layer(const softmax_layer layer, network_state state)
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{
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int b;
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int inputs = layer.inputs / layer.groups;
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int batch = layer.batch * layer.groups;
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for(b = 0; b < batch; ++b){
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softmax_array(state.input+b*inputs, inputs, layer.output+b*inputs);
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}
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}
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void backward_softmax_layer(const softmax_layer layer, network_state state)
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{
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int i;
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for(i = 0; i < layer.inputs*layer.batch; ++i){
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state.delta[i] = layer.delta[i];
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}
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}
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