chainer.functions.decorrelated_batch_normalization¶

chainer.functions.
decorrelated_batch_normalization
(x, *, groups=16, eps=2e5, running_mean=None, running_projection=None, decay=0.9)[source]¶ Decorrelated batch normalization function.
It takes the input variable
x
and normalizes it using batch statistics to make the output zeromean and decorrelated. Parameters
x (
Variable
) – Input variable.groups (int) – Number of groups to use for group whitening.
eps (float) – Epsilon value for numerical stability.
running_mean (Ndimensional array) – Expected value of the mean. This is a running average of the mean over several minibatches using the decay parameter. If
None
, the expected mean is initialized to zero.running_projection (Ndimensional array) – Expected value of the project matrix. This is a running average of the projection over several minibatches using the decay parameter. If
None
, the expected projected is initialized to the identity matrix.decay (float) – Decay rate of moving average. It is used during training.
 Returns
The output variable which has the same shape as \(x\).
 Return type
See: Decorrelated Batch Normalization
See also