GSgnnLinkPredictionPredefinedTestDataLoader

class graphstorm.dataloading.GSgnnLinkPredictionPredefinedTestDataLoader(dataset, target_idx, batch_size, fixed_edge_dst_negative_field, fanout=None, fixed_test_size=None, node_feats=None, edge_feats=None, pos_graph_edge_feats=None)

Bases: GSgnnLinkPredictionTestDataLoader

Mini-batch dataloader for link prediction validation and test with predefined negatives.

Parameters

dataset: GSgnnData

The GraphStorm data.

target_idxdict of Tensors

The target edge indexes for link prediction.

batch_size: int

Mini-batch size.

fanout: list of int, or dict of list

Neighbor sampling fanout. If it’s a dict of list, it indicates the fanout for each edge type.

fixed_test_size: int

Fixed number of test data used in evaluation. If it is none, use the whole testset. When test is huge, using fixed_test_size can save validation and test time. Default: None.

fixed_edge_dst_negative_field: str, or list of str

The feature fields that store the fixed negative set for each edge.

node_feats: str, or dict of list of str

Node feature fileds in three possible formats:

• string: All nodes have the same feature name.

• list of string: All nodes have the same list of features.

• dict of list of string: Each node type have different set of node features.

Default: None.

edge_feats: str, or dict of list of str

Edge feature fileds in three possible formats:

• string: All edges have the same feature name.

• list of string: All edges have the same list of features.

• dict of list of string: Each edge type have different set of edge features.

Default: None.

pos_graph_edge_feats: str, or dict of list of str

The edge feature fields used by positive graph in link prediction. For example edge weight. Default: None.