k_dropout

fraction of the entries in the tensor that will be set to 0.

level

shape for randomly generated keep/drop flags, must be
broadcastable to the shape of <code>x</code>

noise_shape

random seed to ensure determinism.

seed

Sets entries in <code>x</code> to zero at random, while scaling the entire tensor.

Interface to 'Keras' <https://keras.io>, a high-level neural
networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation,
supports both convolution based networks and recurrent networks (as well as
combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.

JJ Allaire

keras

R Interface to 'Keras'

Fran<c3><a7>ois Chollet

 RStudio

 Google

Yuan Tang

Daniel Falbel

Wouter Van Der Bijl

Martin Studer

Sigrid Keydana

k_dropout function

This function is part of a set of Keras backend functions that enable
lower level access to the core operations of the backend tensor engine
(e.g. TensorFlow, CNTK, Theano, etc.).
You can see a list of all available backend functions here:
<a href="https://keras.rstudio.com/articles/backend.html#backend-functions">https://keras.rstudio.com/articles/backend.html#backend-functions</a>.

k_dropout: Sets entries in `x` to zero at random, while scaling the entire tensor.

Description

Usage

Arguments

Value

Keras Backend