@ste I agree with all of the above, but an easier way to do it is like so, if you don’t want to deal with a lot of that train_dl.new stuff (easier in my head)
After ll.transform:
ll.valid = ll.train
db = ll.databunch()
learn.data.valid_dl = db.valid_dl
# Create Databunch
il = ImageList.from_folder(path=data_path)
ils = il.split_none() #All data on Train Set
ll = ils.label_from_folder()
ll.valid = ll.train # @muellerzr Trick!
ll.transform(tfms=None,size=256) # Optional Transforms
data = ll.databunch(bs=32);
data.normalize(stats)
learn.data.valid_dl = data.valid_dl
# Interpret
interp = ClassificationInterpretation.from_learner(learn,ds_type=DatasetType.Valid)
interp.plot_confusion_matrix()