gigl.distributed.sampler#

Classes#

ABLPNodeSamplerInput

Sampler input specific for ABLP use case. Contains additional information about positive labels, negative labels, and the corresponding

Module Contents#

class gigl.distributed.sampler.ABLPNodeSamplerInput(node, input_type, positive_labels, negative_labels, supervision_node_type)[source]#

Bases: graphlearn_torch.sampler.NodeSamplerInput

Sampler input specific for ABLP use case. Contains additional information about positive labels, negative labels, and the corresponding supervision node type

Parameters:

  • node (torch.Tensor) – Anchor nodes to fanout from

  • input_type (Optional[Union[str, NodeType]]) – Node type of the anchor nodes

  • positive_labels (torch.Tensor) – Positive label nodes to fanout from

  • negative_labels (Optional[torch.Tensor]) – Negative label nodes to fanout from

  • supervision_node_type (Optional[Union[str, NodeType]]) – Node type of the positive and negative labels. GiGL currently only supports one supervision node type, this may be revisited in the future

negative_labels[source]#
positive_labels[source]#
supervision_node_type[source]#