Bind together a
valid_dl and optionally a
test_dl, ensures they are on
device and apply to them
tfms as batch are drawn.
path is used internally to store temporary files,
collate_fn is passed to the pytorch
Dataloader (replacing the one there) to explain how to collate the samples picked for a batch. By default, it applies data to the object sent (see in
vision.image why this can be important).
An example of
tfms to pass is normalization.
valid_dl and optionally
test_dl will be wrapped in
valid_ds and optionally
test_ds, with batch size
bs and by using
device are passed to the init method.
Adds a transform to all dataloaders.
Put the batches of
device after applying an optional list of
collate_fn will replace the one of
dl. All dataloaders of a
DataBunch are of this type.
Add a transform (i.e. same as
Remove a transform.
Enum= [Train, Valid, Test, Single]
Internal enumerator to name the training, validation and test dataset/dataloader.