torch_geometric.datasets.AMiner

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

Bases: InMemoryDataset

The heterogeneous AMiner dataset from the “metapath2vec: Scalable Representation Learning for Heterogeneous Networks” paper, consisting of nodes from type "paper", "author" and "venue". Venue categories and author research interests are available as ground truth labels for a subset of nodes.

Parameters:

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

  • transform (Optional[Callable], default: None) – A function/transform that takes in a torch_geometric.data.HeteroData object and returns a transformed version. The data object will be transformed before every access.

  • pre_transform (Optional[Callable], default: None) – A function/transform that takes in a torch_geometric.data.HeteroData object and returns a transformed version. The data object will be transformed before being saved to disk.

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