Create from imagenet style dataset in `path` with `train`,`valid`,`test` subfolders (or provide `valid_pct`).

def from_folder(cls, path:PathOrStr, train:PathOrStr='train', valid:PathOrStr='valid',
                    valid_pct=None, classes:Collection=None, **kwargs:Any)->'ImageDataBunch':
        "Create from imagenet style dataset in `path` with `train`,`valid`,`test` subfolders (or provide `valid_pct`)."
        path=Path(path)
        il = ImageList.from_folder(path)
        if valid_pct is None: src = il.split_by_folder(train=train, valid=valid)
        else: src = il.split_by_rand_pct(valid_pct)
        src = src.label_from_folder(classes=classes)
        return cls.create_from_ll(src, **kwargs)