title: How to add Gaussian noise with varying std during training?
body: <p>I am training a CNN using keras and tensorflow. I would like to add Gaussian noise to my input data during training and reduce the percentage of the noise in further steps. What I do right now, I use:</p>
  <pre><code>from tensorflow.python.keras.layers import Input, GaussianNoise, BatchNormalization
  inputs = Input(shape=x_train_n.shape[1:])
  bn0 = BatchNormalization(axis=1, scale=True)(inputs)
  g0 = GaussianNoise(0.5)(bn0) 
  </code></pre>
  <p>The variable that GaussianNoise takes is the standard deviation of the noise distribution and I couldn't assign a dynamic value to it, how can I add for example a noise, and then decrease this value based on the epoch that I am in?</p>