Developer Guide

Contents

Softmax Forward Layer

For any
x
i
1
...
i
p
from
X
R
n
1
x ... x
n
p
and dimension
k
of size
n
k
, the forward softmax layer for computes the function defined as
The softmax function is known as the normalized exponential (see [ Bishop2006 ] for exact definitions of softmax).

Problem Statement

Given a
p
-dimensional tensor
X
of size
n
1
x
n
2
x ... x
n
p
, the problem is to compute the
p
-dimensional tensor
Y
= (
y
i
1
...
i
p
) of size
n
1
x
n
2
x ... x
n
p
such that:
The library supports the numerically stable version of the softmax function:
where

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804