torch_geometric.datasets.Planetoid

class Planetoid(root: str, name: str, split: str = 'public', num_train_per_class: int = 20, num_val: int = 500, num_test: int = 1000, transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None)[source]

Bases: InMemoryDataset

The citation network datasets "Cora", "CiteSeer" and "PubMed" from the “Revisiting Semi-Supervised Learning with Graph Embeddings” paper. Nodes represent documents and edges represent citation links. Training, validation and test splits are given by binary masks.

Parameters

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

  • name (str) – The name of the dataset ("Cora", "CiteSeer", "PubMed").

  • split (str, optional) –

    The type of dataset split ("public", "full", "geom-gcn", "random"). If set to "public", the split will be the public fixed split from the “Revisiting Semi-Supervised Learning with Graph Embeddings” paper. If set to "full", all nodes except those in the validation and test sets will be used for training (as in the “FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling” paper). If set to "geom-gcn", the 10 public fixed splits from the “Geom-GCN: Geometric Graph Convolutional Networks” paper are given. If set to "random", train, validation, and test sets will be randomly generated, according to num_train_per_class, num_val and num_test. (default: "public")

  • num_train_per_class (int, optional) – The number of training samples per class in case of "random" split. (default: 20)

  • num_val (int, optional) – The number of validation samples in case of "random" split. (default: 500)

  • num_test (int, optional) – The number of test samples in case of "random" split. (default: 1000)

  • 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)

STATS:

Name

#nodes

#edges

#features

#classes

Cora

2,708

10,556

1,433

7

CiteSeer

3,327

9,104

3,703

6

PubMed

19,717

88,648

500

3