Developer Guide

Contents

Local Contrast Normalization Forward Layer

Given a
p
-dimensional tensor
X
R
n
1
x
n
2
x ... x
n
p
, two-dimensional tensor
K
R
m
1
x
m
2
, dimensions
k
1
of size
m
1
and
k
2
of size
m
2
, and dimension
f
different from
k
1
and
k
2
, the layer computes the
p
-dimensional tensor
Y
R
n
1
x
n
2
x ... x
n
p
such that:
See [Jarrett2009] for an exact definition of local contrast normalization.
The library supports four-dimensional input tensors
X
R
n
1
x
n
2
x
n
3
x
n
4
.

Problem Statement

Without loss of generality let's assume that forward local contrast normalization is applied to the last two dimensions.
The problem is to compute the tensor
Y
depending on whether the dimension
f
is set:
  • Dimension
    f
    is set; let it be
    n
    2
    :
    where elements of the weighting window are normalized by the library through dimension
    f
    to meet the condition:
  • Dimension
    f
    is not set:
    where the weighting window meets the condition

Product and Performance Information

1

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Notice revision #20110804