InstanceNormalizationLayer | R Documentation |
Creates an instance normalization layer as described in the paper
https://arxiv.org/abs/1701.02096
with the implementation ported from the following python implementation
an instance normalization layer
Integer specifying which axis should be normalized, typically
the feature axis. For example, after a Conv2D layer with
channels_first
, set axis = 2. Setting axis=-1L
will
normalize all values in each instance of the batch. Axis 1
is the batch dimension for tensorflow backend so we throw an
error if axis = 1
.
Small float added to the variance to avoid dividing by 0.
If TRUE, add beta
offset to normalized tensor.
If TRUE, multiply by gamma
.
Intializer for the beta weight.
Intializer for the gamma weight.
Regularizer for the beta weight.
Regularizer for the gamma weight.
Optional constraint for the beta weight.
Optional constraint for the gamma weight.
$initialize
instantiates a new class.
$call
main body.
$compute_output_shape
computes the output shape.
Tustison NJ
InstanceNormalizationLayer$new()
InstanceNormalizationLayer$new(axis = 2L)
testthat::expect_error(InstanceNormalizationLayer$new(axis = 1L))
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