Batch
A trainable Batch Normalization transform, as described in https://arxiv.org/abs/1502.03167 . When training is complete, use its @see inferenceMode property to get the computed affine transform. This version is provided to imitate the behavior in V1, the previous implementation, in that it calculates a running mean and running variance rather than gathering the raw input to compute the mean and variance. It applies Bessel's correction (https://en.wikipedia.org/wiki/Bessel%27s_correction) to the sample variance to get an estimate of the population variance for each batch, and uses an exponential moving average of those values as an estimate the population variance when @see inferenceMode is applied.
Epsilon is hardcoded to 1.e-5f
Types
Functions
Helper to check that the layer was called with a single input. Returns that input if successful, else errors.
The wrap function should return the same static type it is declared on.