message: Fix the training and inference equations and make them more readable
  Replace the denominators in the equations with their square roots.
  And make the multiplication of gamma a little more readable.
diff: @@ -54,7 +54,7 @@ class BatchNormalizationBase(Layer):
  with the argument `training=True`), the layer normalizes its output using
  the mean and standard deviation of the current batch of inputs. That is to
  say, for each channel being normalized, the layer returns
  - `(batch - mean(batch)) / (var(batch) + epsilon) * gamma + beta`, where:
  + `gamma * (batch - mean(batch)) / sqrt(var(batch) + epsilon) + beta`, where:
  - `epsilon` is small constant (configurable as part of the constructor
  arguments)
  @@ -68,7 +68,7 @@ class BatchNormalizationBase(Layer):
  default), the layer normalizes its output using a moving average of the
  mean and standard deviation of the batches it has seen during training. That
  is to say, it returns
  - `(batch - self.moving_mean) / (self.moving_var + epsilon) * gamma + beta`.
  + `gamma * (batch - self.moving_mean) / sqrt(self.moving_var + epsilon) + beta`.
  `self.moving_mean` and `self.moving_var` are non-trainable variables that
  are updated each time the layer in called in training mode, as such:
  