cugraph_pyg.loader.node_loader.NodeLoader#

class cugraph_pyg.loader.node_loader.NodeLoader(data: Data | HeteroData | Tuple[FeatureStore, GraphStore], node_sampler: BaseSampler, input_nodes: Tensor | None | str | Tuple[str, Tensor | None] = None, input_time: Tensor | None = None, transform: Callable | None = None, transform_sampler_output: Callable | None = None, filter_per_worker: bool | None = None, custom_cls: HeteroData | None = None, input_id: Tensor | None = None, batch_size: int = 1, shuffle: bool = False, drop_last: bool = False, **kwargs)[source]#

Duck-typed version of torch_geometric.loader.NodeLoader. Loads samples from batches of input nodes using a ~cugraph_pyg.sampler.BaseSampler.sample_from_nodes function.

__init__(data: Data | HeteroData | Tuple[FeatureStore, GraphStore], node_sampler: BaseSampler, input_nodes: Tensor | None | str | Tuple[str, Tensor | None] = None, input_time: Tensor | None = None, transform: Callable | None = None, transform_sampler_output: Callable | None = None, filter_per_worker: bool | None = None, custom_cls: HeteroData | None = None, input_id: Tensor | None = None, batch_size: int = 1, shuffle: bool = False, drop_last: bool = False, **kwargs)[source]#

Parameters:

data: Data, HeteroData, or Tuple[FeatureStore, GraphStore]

See torch_geometric.loader.NodeLoader.

node_sampler: BaseSampler

See torch_geometric.loader.NodeLoader.

input_nodes: InputNodes

See torch_geometric.loader.NodeLoader.

input_time: OptTensor

See torch_geometric.loader.NodeLoader.

transform: Callable (optional, default=None)

This argument currently has no effect.

transform_sampler_output: Callable (optional, default=None)

This argument currently has no effect.

filter_per_worker: bool (optional, default=False)

This argument currently has no effect.

custom_cls: HeteroData

This argument currently has no effect. This loader will always return a Data or HeteroData object.

input_id: OptTensor

See torch_geometric.loader.NodeLoader.

Methods

__init__(data, node_sampler[, input_nodes, ...])