Rotate Augmentation

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

Being an augment_ operator, its stages parameter starts out as "train", so the augmentation is applied while training and not when predicting. Set stages = "both" to apply it in both phases. See PipeOpTaskPreprocTorch for the stages parameter and this naming convention.

Format

R6Class inheriting from PipeOpTaskPreprocTorch.

Construction

po("augment_rotate")

Parameters

Id	Type	Default	Levels	Range
angle	untyped	-		-
resample	integer	0		\((-\infty, \infty)\)
expand	logical	FALSE	TRUE, FALSE	-
center	untyped	NULL		-
fill	untyped	NULL		-
stages	character	-	train, predict, both	-
affect_columns	untyped	selector_all()		-