activation_hard_silu

activation_hard_swish

It is defined as:<ul>
<li><code>0</code> if <code>if x &lt; -3</code></li>
<li><code>x</code> if <code>x &gt; 3</code></li>
<li><code>x * (x + 3) / 6</code> if <code>-3 &lt;= x &lt;= 3</code></li>
</ul>It's a faster, piecewise linear approximation of the silu activation.

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.

Tomasz Kalinowski

keras3

R Interface to 'Keras'

Daniel Falbel

JJ Allaire

François Chollet

Posit Software, PBC 

Google 

Yuan Tang

Wouter Van Der Bijl

Martin Studer

Sigrid Keydana

activation_hard_silu function

<dl><dt>x</dt>
<dd>Input tensor.</dd></dl>

Arguments

<ul>
<li><a href="https://arxiv.org/abs/1905.02244">A Howard, 2019</a></li>
</ul>

Reference

It is defined as:<ul>
<li><code>0</code> if <code>if x &lt; -3</code></li>
<li><code>x</code> if <code>x &gt; 3</code></li>
<li><code>x * (x + 3) / 6</code> if <code>-3 &lt;= x &lt;= 3</code></li>
</ul>

It's a faster, piecewise linear approximation of the silu activation.

Hard SiLU activation function, also known as Hard Swish. — activation_hard_silu

<dl>

<dt>x</dt>
<dd>Input tensor.</dd>

</dl>

<ul>
<li><a href='https://arxiv.org/abs/1905.02244'>A Howard, 2019</a></li>
</ul>

activation_hard_silu: Hard SiLU activation function, also known as Hard Swish.

Description

Usage

Value

Arguments

Reference