gigl.types.PartitionOutput

class gigl.types.distributed.PartitionOutput(node_partition_book: Union[graphlearn_torch.partition.base.PartitionBook, dict[NewType.<locals>.new_type, graphlearn_torch.partition.base.PartitionBook]], edge_partition_book: Union[graphlearn_torch.partition.base.PartitionBook, dict[gigl.src.common.types.graph_data.EdgeType, graphlearn_torch.partition.base.PartitionBook]], partitioned_edge_index: Union[gigl.types.distributed.GraphPartitionData, dict[gigl.src.common.types.graph_data.EdgeType, gigl.types.distributed.GraphPartitionData], NoneType], partitioned_node_features: Union[gigl.types.distributed.FeaturePartitionData, dict[NewType.<locals>.new_type, gigl.types.distributed.FeaturePartitionData], NoneType], partitioned_edge_features: Union[gigl.types.distributed.FeaturePartitionData, dict[gigl.src.common.types.graph_data.EdgeType, gigl.types.distributed.FeaturePartitionData], NoneType], partitioned_positive_labels: Union[torch.Tensor, dict[gigl.src.common.types.graph_data.EdgeType, torch.Tensor], NoneType], partitioned_negative_labels: Union[torch.Tensor, dict[gigl.src.common.types.graph_data.EdgeType, torch.Tensor], NoneType])

Bases: object

Methods

__init__

__eq__(other)

Return self==value.

__hash__ = None

__init__(node_partition_book: PartitionBook | dict[NodeType, PartitionBook], edge_partition_book: PartitionBook | dict[EdgeType, PartitionBook], partitioned_edge_index: GraphPartitionData | dict[EdgeType, GraphPartitionData] | None, partitioned_node_features: FeaturePartitionData | dict[NodeType, FeaturePartitionData] | None, partitioned_edge_features: FeaturePartitionData | dict[EdgeType, FeaturePartitionData] | None, partitioned_positive_labels: Tensor | dict[EdgeType, Tensor] | None, partitioned_negative_labels: Tensor | dict[EdgeType, Tensor] | None) → None

__repr__()

Return repr(self).

__weakref__

list of weak references to the object (if defined)