Normalization Transformation

Calls torchvision::transform_normalize, see there for more information on the parameters. The preprocessing is applied to each element of a batch individually.

Being a trafo_ operator, its stages parameter starts out as "both", so the transformation is applied both while training and when predicting. Set stages = "train" to restrict it to training. See PipeOpTaskPreprocTorch for the stages parameter and this naming convention.

Format

R6Class inheriting from PipeOpTaskPreprocTorch.

Construction

po("trafo_normalize")

Parameters

Id	Type	Default	Levels
mean	untyped	-
std	untyped	-
stages	character	-	train, predict, both
affect_columns	untyped	selector_all()