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")