torch_geometric.datasets.MalNetTiny

class MalNetTiny(root: str, split: Optional[str] = None, transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None, pre_filter: Optional[Callable] = None, force_reload: bool = False)[source]

Bases: InMemoryDataset

The MalNet Tiny dataset from the “A Large-Scale Database for Graph Representation Learning” paper. MalNetTiny contains 5,000 malicious and benign software function call graphs across 5 different types. Each graph contains at most 5k nodes.

Parameters:

  • root (str) – Root directory where the dataset should be saved.

  • split (str, optional) – If "train", loads the training dataset. If "val", loads the validation dataset. If "trainval", loads the training and validation dataset. If "test", loads the test dataset. If None, loads the entire dataset. (default: None)

  • transform (callable, optional) – A function/transform that takes in an torch_geometric.data.Data object and returns a transformed version. The data object will be transformed before every access. (default: None)

  • pre_transform (callable, optional) – A function/transform that takes in an torch_geometric.data.Data object and returns a transformed version. The data object will be transformed before being saved to disk. (default: None)

  • pre_filter (callable, optional) – A function that takes in an torch_geometric.data.Data object and returns a boolean value, indicating whether the data object should be included in the final dataset. (default: None)

  • force_reload (bool, optional) – Whether to re-process the dataset. (default: False)