function batchNormalization$1(args) {
	  return new BatchNormalization(args);
	}
Batch normalization layer (Ioffe and Szegedy, 2014).

Normalize the activations of the previous layer at each batch,
i.e. applies a transformation that maintains the mean activation
close to 0 and the activation standard deviation close to 1.

Input shape:
  Arbitrary. Use the keyword argument `inputShape` (Array of integers, does
  not include the sample axis) when calling the constructor of this class,
  if this layer is used as a first layer in a model.

Output shape:
  Same shape as input.

References:
  - [Batch Normalization: Accelerating Deep Network Training by Reducing
Internal Covariate Shift](https://arxiv.org/abs/1502.03167)

@doc {heading: 'Layers', subheading: 'Normalization', namespace: 'layers'}