def __init__(self, prm):
self.data_source = prm.data_source
self.data_transform = prm.data_transform
self.data_path = prm.data_path
if self.data_source == 'Omniglot':
# Randomly split the characters to meta-train and meta-test
# Later, tasks will be generated using this characters
self.chars_splits = omniglot.split_chars(prm.data_path, prm.chars_split_type, prm.n_meta_train_chars)
elif self.data_source == 'SmallImageNet':
self.class_split = imagenet_data.split_classes(prm)
def __init__(self, prm):
self.data_source = prm.data_source
self.data_transform = prm.data_transform
self.data_path = prm.data_path
if self.data_source == 'Omniglot':
# Randomly split the characters to meta-train and meta-test
# Later, tasks will be generated using this characters
self.chars_splits = omniglot.split_chars(prm.data_path,
prm.chars_split_type,
prm.n_meta_train_chars)
#elif self.data_source == 'SmallImageNet':
# self.class_split = imagenet_data.split_classes(prm)
elif self.data_source == 'Caltech256':
self.class_split = Caltech256.split_classes()
elif self.data_source == 'CIFAR100':
self.class_split = cifar100.split_classes()
else:
raise Exception("No such dataset")