tf.keras.layers.GaussianDropout | TensorFlow v2.0.0 (original) (raw)
tf.keras.layers.GaussianDropout
Stay organized with collections Save and categorize content based on your preferences.
Apply multiplicative 1-centered Gaussian noise.
Inherits From: Layer
View aliases
Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.keras.layers.GaussianDropout
tf.keras.layers.GaussianDropout(
rate, **kwargs
)
As it is a regularization layer, it is only active at training time.
| Arguments | |
|---|---|
| rate | Float, drop probability (as with Dropout). The multiplicative noise will have standard deviation sqrt(rate / (1 - rate)). |
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.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2020-10-01 UTC.