Resizing Transformation

Calls torchvision::transform_resize, see there for more information on the parameters. The preprocessing is applied to the whole batch.

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_resize")

Parameters

Id	Type	Default	Levels
size	untyped	-
interpolation	character	2	Undefined, Bartlett, Blackman, Bohman, Box, Catrom, Cosine, Cubic, Gaussian, Hamming, [...]
stages	character	-	train, predict, both
affect_columns	untyped	selector_all()