CoraFullDataset๏ƒ

class dgl.data.CoraFullDataset(raw_dir=None, force_reload=False, verbose=False, transform=None)[source]๏ƒ

Bases: GNNBenchmarkDataset

CORA-Full dataset for node classification task.

Extended Cora dataset. Nodes represent paper and edges represent citations.

Reference: https://github.com/shchur/gnn-benchmark#datasets

Statistics:

  • Nodes: 19,793

  • Edges: 126,842 (note that the original dataset has 65,311 edges but DGL adds the reverse edges and remove the duplicates, hence with a different number)

  • Number of Classes: 70

  • Node feature size: 8,710

Parameters:

  • raw_dir (str) โ€“ Raw file directory to download/contains the input data directory. Default: ~/.dgl/

  • force_reload (bool) โ€“ Whether to reload the dataset. Default: False

  • verbose (bool) โ€“ Whether to print out progress information. Default: True.

  • transform (callable, optional) โ€“ A transform that takes in a DGLGraph object and returns a transformed version. The DGLGraph object will be transformed before every access.

num_classes๏ƒ

Number of classes for each node.

Type:

int

Examples

>>> data = CoraFullDataset()
>>> g = data[0]
>>> num_class = data.num_classes
>>> feat = g.ndata['feat']  # get node feature
>>> label = g.ndata['label']  # get node labels
__getitem__(idx)๏ƒ

Get graph by index

Parameters:

idx (int) โ€“ Item index

Returns:

The graph contains:

  • ndata['feat']: node features

  • ndata['label']: node labels

Return type:

dgl.DGLGraph

__len__()๏ƒ

Number of graphs in the dataset