# chainer.functions.decorrelated_batch_normalization¶

chainer.functions.decorrelated_batch_normalization(x, *, groups=16, eps=2e-05, 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 zero-mean 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 (N-dimensional array) – Expected value of the mean. This is a running average of the mean over several mini-batches using the decay parameter. If None, the expected mean is initialized to zero.

• running_projection (N-dimensional array) – Expected value of the project matrix. This is a running average of the projection over several mini-batches 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

Variable