tf.keras.layers.GaussianDropout(rate, seed=None, **kwargs)
Apply multiplicative 1-centered Gaussian noise.
As it is a regularization layer, it is only active at training time.
Dropout). The multiplicative noise will have standard deviation
sqrt(rate / (1 - rate)).
Arbitrary. Use the keyword argument
(tuple of integers, does not include the samples axis)
when using this layer as the first layer in a model.
Same shape as input.