tf.keras.layers.GaussianDropout

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Apply multiplicative 1-centered Gaussian noise.

Inherits From: Layer, Operation

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).

Attributes
input	Retrieves the input tensor(s) of a symbolic operation. Only returns the tensor(s) corresponding to the first time the operation was called.
output	Retrieves the output tensor(s) of a layer. Only returns the tensor(s) corresponding to the first time the operation was called.

Methods

from_config

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@classmethod
from_config(
    config
)

Creates a layer from its config.

This method is the reverse of get_config, capable of instantiating the same layer from the config dictionary. It does not handle layer connectivity (handled by Network), nor weights (handled by set_weights).

Args
config	A Python dictionary, typically the output of get_config.

Returns
A layer instance.

symbolic_call

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symbolic_call(
    *args, **kwargs
)