Index: webrtc/modules/audio_coding/codecs/opus/opus/src/src/mlp_train.h |
diff --git a/webrtc/modules/audio_coding/codecs/opus/opus/src/src/mlp_train.h b/webrtc/modules/audio_coding/codecs/opus/opus/src/src/mlp_train.h |
new file mode 100644 |
index 0000000000000000000000000000000000000000..2786b40d8ba07ee41014bdc470e96bcb8fddf55a |
--- /dev/null |
+++ b/webrtc/modules/audio_coding/codecs/opus/opus/src/src/mlp_train.h |
@@ -0,0 +1,86 @@ |
+/* 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. |
+ |
+ - Redistributions in binary form must reproduce the above copyright |
+ notice, this list of conditions and the following disclaimer in the |
+ documentation and/or other materials provided with the distribution. |
+ |
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
+ ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
+ LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
+ A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE FOUNDATION OR |
+ CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, |
+ EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, |
+ PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR |
+ PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF |
+ LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING |
+ NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS |
+ 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) |
+{ |
+ 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)); |
+} |
+ |
+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; |
+} |
+ |
+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; |
+} MLPTrain; |
+ |
+ |
+#endif /* _MLP_TRAIN_H_ */ |