chmncc.dataset package

Submodules

chmncc.dataset.dataloaders module

chmncc.dataset.datasets module

Original datasets metadata: Giunchiglia et al approach

chmncc.dataset.load_cifar module

chmncc.dataset.load_dataset module

chmncc.dataset.load_dataset_factory module

chmncc.dataset.load_debug_dataset module

chmncc.dataset.load_fashion_mnist module

chmncc.dataset.load_mnist module

chmncc.dataset.load_omniglot module

chmncc.dataset.parser module

Original parser This code was adapted from https://github.com/lucamasera/AWX

class chmncc.dataset.parser.arff_data(arff_file, is_GO, is_test=False)

Bases: object

All the datasets they provide are in arff, this is the class

chmncc.dataset.parser.initialize_dataset(name: str, datasets: Dict[str, Tuple[bool, str, str, str]]) → Tuple[arff_data, arff_data, arff_data]

Initialize the dataset

Parameters:

• [str] (name) – name of the dataset to prepare

• Dict[List[bool (datasets) – whether the dataset is GO, the train,

• str – whether the dataset is GO, the train,

• str – whether the dataset is GO, the train,

• str]] – whether the dataset is GO, the train,

• location (validation and test data) –

Returns:

train dataset [arff_data] validation dataset [arff_data] test dataset [arff_data]

chmncc.dataset.parser.initialize_other_dataset(name: str, datasets: Dict[str, Tuple[bool, str, str]]) → Tuple[arff_data, arff_data]

Initialize the dataset

Parameters:

• [str] (name) – name of the dataset to prepare

• [bool (datasets) – whether the dataset is go (?), the train

• str – whether the dataset is go (?), the train

• str] – whether the dataset is go (?), the train

• location (and test data) –

Returns:

train dataset [arff_data] test dataset [arff_data]

chmncc.dataset.parser.parse_arff(arff_file: str, is_GO=False, is_test=False) → Tuple[Tensor, Tensor, Tensor, DiGraph]

Parse the arff data

Parameters:

• [str] (arf_file) – arff file

• [bool] (is_test) – whether it is the GO dataset

• [bool] – whether the dataset is test

Returns:

X [torch.Tensor] data instances Y [torch.Tensor] labels R [torch.Tensor[torch.Tensor]] adjacency matrix g [nx.DiGraph] graph

chmncc.dataset.preproces_cifar module

chmncc.dataset.visualize_dataset module

Module contents