From 0f645836f193e75c4c3b718369e6fab15b5d19c5 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 11 Feb 2015 03:41:03 +0000
Subject: [PATCH] Detection is back, baby\!

---
 src/softmax_layer.c |   43 ++++++++++++++++++++++++++++++-------------
 1 files changed, 30 insertions(+), 13 deletions(-)

diff --git a/src/softmax_layer.c b/src/softmax_layer.c
index b213e5b..aa5ab06 100644
--- a/src/softmax_layer.c
+++ b/src/softmax_layer.c
@@ -1,34 +1,51 @@
 #include "softmax_layer.h"
+#include "blas.h"
+#include "cuda.h"
+#include <float.h>
 #include <math.h>
 #include <stdlib.h>
 #include <stdio.h>
 
-softmax_layer *make_softmax_layer(int inputs)
+softmax_layer *make_softmax_layer(int batch, int inputs)
 {
     fprintf(stderr, "Softmax Layer: %d inputs\n", inputs);
     softmax_layer *layer = calloc(1, sizeof(softmax_layer));
+    layer->batch = batch;
     layer->inputs = inputs;
-    layer->output = calloc(inputs, sizeof(double));
-    layer->delta = calloc(inputs, sizeof(double));
+    layer->output = calloc(inputs*batch, sizeof(float));
+    layer->delta = calloc(inputs*batch, sizeof(float));
+    layer->jacobian = calloc(inputs*inputs*batch, sizeof(float));
+    #ifdef GPU
+    layer->output_gpu = cuda_make_array(layer->output, inputs*batch); 
+    layer->delta_gpu = cuda_make_array(layer->delta, inputs*batch); 
+    #endif
     return layer;
 }
 
-void forward_softmax_layer(const softmax_layer layer, double *input)
+void forward_softmax_layer(const softmax_layer layer, float *input)
 {
-    int i;
-    double sum = 0;
-    for(i = 0; i < layer.inputs; ++i){
-        sum += exp(input[i]);
-    }
-    for(i = 0; i < layer.inputs; ++i){
-        layer.output[i] = exp(input[i])/sum;
+    int i,b;
+    for(b = 0; b < layer.batch; ++b){
+        float sum = 0;
+        float largest = -FLT_MAX;
+        for(i = 0; i < layer.inputs; ++i){
+            if(input[i+b*layer.inputs] > largest) largest = input[i+b*layer.inputs];
+        }
+        for(i = 0; i < layer.inputs; ++i){
+            sum += exp(input[i+b*layer.inputs]-largest);
+        }
+        if(sum) sum = largest+log(sum);
+        else sum = largest-100;
+        for(i = 0; i < layer.inputs; ++i){
+            layer.output[i+b*layer.inputs] = exp(input[i+b*layer.inputs]-sum);
+        }
     }
 }
 
-void backward_softmax_layer(const softmax_layer layer, double *input, double *delta)
+void backward_softmax_layer(const softmax_layer layer, float *delta)
 {
     int i;
-    for(i = 0; i < layer.inputs; ++i){
+    for(i = 0; i < layer.inputs*layer.batch; ++i){
         delta[i] = layer.delta[i];
     }
 }

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