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
A fake dataset that returns randomly generated
HeteroData
objects.- Parameters:
num_graphs (int, optional) – The number of graphs. (default:
1
)num_node_types (int, optional) – The number of node types. (default:
3
)num_edge_types (int, optional) – The number of edge types. (default:
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) – The average number of node features. (default:
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 ifnum_graphs > 1
, and node-level labels other-wise. (default:"auto"
)transform (callable, optional) – A function/transform that takes in an
torch_geometric.data.HeteroData
object and returns a transformed version. The data object will be transformed before every access. (default:None
)**kwargs (optional) – Additional attributes and their shapes e.g.
global_features=5
.