message: Clarify batch norm parameter documentation.
diff: @@ -502,11 +502,21 @@ message ConcatParameter {
  }
  message BatchNormParameter {
  - // If false, accumulate global mean/variance values via a moving average. If
  - // true, use those accumulated values instead of computing mean/variance
  - // across the batch.
  + // If false, normalization is performed over the current mini-batch
  + // and global statistics are accumulated (but not yet used) by a moving
  + // average.
  + // If true, those accumulated mean and variance values are used for the
  + // normalization.
  + // By default, it is set to false when the network is in the training
  + // phase and true when the network is in the testing phase.
  optional bool use_global_stats = 1;
  - // How much does the moving average decay each iteration?
  + // What fraction of the moving average remains each iteration?
  + // Smaller values make the moving average decay faster, giving more
  + // weight to the recent values.
  + // Each iteration updates the moving average @f$S_{t-1}@f$ with the
  + // current mean @f$ Y_t @f$ by
  + // @f$ S_t = (1-\beta)Y_t + \beta \cdot S_{t-1} @f$, where @f$ \beta @f$
  + // is the moving_average_fraction parameter.
  optional float moving_average_fraction = 2 [default = .999];
  // Small value to add to the variance estimate so that we don't divide by
  // zero.
  