tf.keras.layers.GaussianDropout

Apply multiplicative 1-centered Gaussian noise.

Inherits From: Layer, Module

Compat aliases for migration

tf.compat.v1.keras.layers.GaussianDropout

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

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

Args
`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.

Call arguments
`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).

Input shape
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.

Output shape
Same shape as input.

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Last updated 2022-10-27 UTC.

Args