Revert "Pull the Voice Activity Detector out from the AGC"

webrtc/modules/audio_processing/agc/gmm.cc

 /*
  *  Copyright (c) 2012 The WebRTC project authors. All Rights Reserved.
  *
  *  Use of this source code is governed by a BSD-style license
  *  that can be found in the LICENSE file in the root of the source
  *  tree. An additional intellectual property rights grant can be found
  *  in the file PATENTS.  All contributing project authors may
  *  be found in the AUTHORS file in the root of the source tree.
  */
 
-#include "webrtc/modules/audio_processing/vad/gmm.h"
+#include "webrtc/modules/audio_processing/agc/gmm.h"
 
 #include <math.h>
 #include <stdlib.h>
 
 #include "webrtc/typedefs.h"
 
 namespace webrtc {
 
 static const int kMaxDimension = 10;
 
-static void RemoveMean(const double* in,
-                       const double* mean_vec,
-                       int dimension,
-                       double* out) {
+static void RemoveMean(const double* in, const double* mean_vec,
+                       int dimension, double* out) {
   for (int n = 0; n < dimension; ++n)
     out[n] = in[n] - mean_vec[n];
 }
 
-static double ComputeExponent(const double* in,
-                              const double* covar_inv,
+static double ComputeExponent(const double* in, const double* covar_inv,
                               int dimension) {
   double q = 0;
   for (int i = 0; i < dimension; ++i) {
     double v = 0;
     for (int j = 0; j < dimension; j++)
       v += (*covar_inv++) * in[j];
     q += v * in[i];
   }
   q *= -0.5;
   return q;
 }
 
 double EvaluateGmm(const double* x, const GmmParameters& gmm_parameters) {
   if (gmm_parameters.dimension > kMaxDimension) {
     return -1;  // This is invalid pdf so the caller can check this.
   }
   double f = 0;
   double v[kMaxDimension];
   const double* mean_vec = gmm_parameters.mean;
   const double* covar_inv = gmm_parameters.covar_inverse;
 
   for (int n = 0; n < gmm_parameters.num_mixtures; n++) {
     RemoveMean(x, mean_vec, gmm_parameters.dimension, v);
     double q = ComputeExponent(v, covar_inv, gmm_parameters.dimension) +
-               gmm_parameters.weight[n];
+        gmm_parameters.weight[n];
     f += exp(q);
     mean_vec += gmm_parameters.dimension;
     covar_inv += gmm_parameters.dimension * gmm_parameters.dimension;
   }
   return f;
 }
 
 }  // namespace webrtc