Update to opus-HEAD-66611f1.

src/mlp_train.h

 /* Copyright (c) 2008-2011 Octasic Inc.
    Written by Jean-Marc Valin */
 /*
    Redistribution and use in source and binary forms, with or without
    modification, are permitted provided that the following conditions
    are met:
 
    - Redistributions of source code must retain the above copyright
    notice, this list of conditions and the following disclaimer.
 
@@ skipping 14 matching lines @@
    SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
 
 #ifndef _MLP_TRAIN_H_
 #define _MLP_TRAIN_H_
 
 #include <math.h>
 #include <stdlib.h>
 
 double tansig_table[501];
-static inline double tansig_double(double x) 
+static inline double tansig_double(double x)
 {
-        return 2./(1.+exp(-2.*x)) - 1.;
+    return 2./(1.+exp(-2.*x)) - 1.;
 }
 static inline void build_tansig_table()
 {
-        int i;
-        for (i=0;i<501;i++)
-                tansig_table[i] = tansig_double(.04*(i-250));
+    int i;
+    for (i=0;i<501;i++)
+        tansig_table[i] = tansig_double(.04*(i-250));
 }
 
 static inline double tansig_approx(double x)
 {
-        int i;
-        double y, dy;
-        if (x>=10)
-                return 1;
-        if (x<=-10)
-                return -1;
-        i = lrint(25*x);
-        x -= .04*i;
-        y = tansig_table[250+i];
-        dy = 1-y*y;
-        y = y + x*dy*(1 - y*x);
-        return y;
+    int i;
+    double y, dy;
+    if (x>=10)
+        return 1;
+    if (x<=-10)
+        return -1;
+    i = lrint(25*x);
+    x -= .04*i;
+    y = tansig_table[250+i];
+    dy = 1-y*y;
+    y = y + x*dy*(1 - y*x);
+    return y;
 }
 
 inline float randn(float sd)
 {
    float U1, U2, S, x;
    do {
       U1 = ((float)rand())/RAND_MAX;
       U2 = ((float)rand())/RAND_MAX;
       U1 = 2*U1-1;
       U2 = 2*U2-1;
       S = U1*U1 + U2*U2;
    } while (S >= 1 || S == 0.0f);
    x = sd*sqrt(-2 * log(S) / S) * U1;
    return x;
 }
 
 
 typedef struct {
-        int layers;
-        int *topo;
-        double **weights;
-        double **best_weights;
-        double *in_rate;
+    int layers;
+    int *topo;
+    double **weights;
+    double **best_weights;
+    double *in_rate;
 } MLPTrain;
 
 
 #endif /* _MLP_TRAIN_H_ */