tf.keras.layers.GaussianDropout

Apply multiplicative 1-centered Gaussian noise.

Inherits From: Layer, Module

tf.keras.layers.GaussianDropout(
    rate, seed=None, **kwargs
)

As it is a regularization layer, it is only active at training time.

rate Float, drop probability (as with Dropout). The multiplicative noise will have standard deviation sqrt(rate / (1 - rate)).
seed Integer, optional random seed to enable deterministic behavior.

inputs Input tensor (of any rank).
training Python boolean indicating whether the layer should behave in training mode (adding dropout) or in inference mode (doing nothing).

Arbitrary. Use the keyword argument input_shape (tuple of integers, does not include the samples axis) when using this layer as the first layer in a model.

Same shape as input.