torch_geometric.datasets.FakeHeteroDataset

class FakeHeteroDataset(num_graphs: int = 1, num_node_types: int = 3, num_edge_types: int = 6, avg_num_nodes: int = 1000, avg_degree: float = 10.0, avg_num_channels: int = 64, edge_dim: int = 0, num_classes: int = 10, task: str = 'auto', transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None, **kwargs: Union[int, Tuple[int, ...]])[source]

Bases: InMemoryDataset

一个返回随机生成的HeteroData对象的假数据集。

Parameters:

  • num_graphs (int, optional) – The number of graphs. (default: 1)

  • num_node_types (int, optional) – 节点类型的数量。 (默认: 3)

  • num_edge_types (int, optional) – 边的类型数量。 (默认: 6)

  • avg_num_nodes (int, optional) – The average number of nodes in a graph. (default: 1000)

  • avg_degree (float, optional) – The average degree per node. (default: 10.0)

  • avg_num_channels (int, optional) – 节点特征的平均数量。 (默认: 64)

  • edge_dim (int, optional) – The number of edge features. (default: 0)

  • num_classes (int, optional) – The number of classes in the dataset. (default: 10)

  • task (str, optional) – Whether to return node-level or graph-level labels ("node", "graph", "auto"). If set to "auto", will return graph-level labels if num_graphs > 1, and node-level labels other-wise. (default: "auto")

  • transform (callable, optional) – 一个函数/转换，它接收一个torch_geometric.data.HeteroData对象并返回一个转换后的版本。数据对象将在每次访问之前进行转换。（默认值：None）

  • **kwargs (optional) – Additional attributes and their shapes e.g. global_features=5.