torch_geometric.datasets.NELL
- class NELL(root: str, transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None)[source]
Bases:
InMemoryDataset
The NELL dataset, a knowledge graph from the “Toward an Architecture for Never-Ending Language Learning” paper. The dataset is processed as in the “Revisiting Semi-Supervised Learning with Graph Embeddings” paper.
Note
Entity nodes are described by sparse feature vectors of type
torch_sparse.SparseTensor
, which can be either used directly, or can be converted viadata.x.to_dense()
,data.x.to_scipy()
ordata.x.to_torch_sparse_csr_tensor()
.- Parameters
root (str) – Root directory where the dataset should be saved.
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:
#nodes
#edges
#features
#classes
65,755
251,550
61,278
186