**dgl.graphbolt** is a dataloading framework for GNN that provides well-defined APIs for each stage of the data pipeline and multiple standard implementations.
**dgl.graphbolt** is a dataloading framework for GNN that provides well-defined
APIs for each stage of the data pipeline and multiple standard implementations.
APIs
Dataset
-------------------------
-------
A dataset is a collection of graph structure data, feature data and tasks.
.. autosummary::
.. autosummary::
:toctree: ../../generated/
:toctree: ../../generated/
:nosignatures:
:nosignatures:
:template: graphbolt_classtemplate.rst
:template: graphbolt_classtemplate.rst
DataLoader
Dataset
Dataset
OnDiskDataset
BuiltinDataset
LegacyDataset
Task
Task
Graph
-----
A graph is a collection of nodes and edges. It can be a homogeneous graph or a
heterogeneous graph.
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: graphbolt_classtemplate.rst
SamplingGraph
FusedCSCSamplingGraph
Feature and FeatureStore
------------------------
A feature is a collection of data(tensor, array). A feature store is a
collection of features.
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: graphbolt_classtemplate.rst
Feature
FeatureStore
BasicFeatureStore
TorchBasedFeature
TorchBasedFeatureStore
GPUCachedFeature
DataLoader
----------
A dataloader is for iterating over a dataset and generate mini-batches.
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: graphbolt_classtemplate.rst
DataLoader
ItemSet
-------
An item set is a iterable collection of items.
.. autosummary::
:toctree: ../../generated/
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:template: graphbolt_classtemplate.rst
ItemSet
ItemSet
ItemSetDict
ItemSetDict
ItemSampler
-----------
An item sampler is for sampling items from an item set.
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: graphbolt_classtemplate.rst
ItemSampler
ItemSampler
DistributedItemSampler
DistributedItemSampler
NegativeSampler
SubgraphSampler
SampledSubgraph
MiniBatch
SamplingGraph
---------
A mini-batch is a collection of sampled subgraphs and their corresponding
features. It is the basic unit for training a GNN model.
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: graphbolt_classtemplate.rst
MiniBatch
MiniBatch
MiniBatchTransformer
DGLMiniBatch
DGLMiniBatch
DGLMiniBatchConverter
DGLMiniBatchConverter
Feature
FeatureStore
FeatureFetcher
CopyTo
Standard Implementations
NegativeSampler
-------------------------
---------------
A negative sampler is for sampling negative items from mini-batches.
.. autosummary::
.. autosummary::
:toctree: ../../generated/
:toctree: ../../generated/
:nosignatures:
:nosignatures:
:template: graphbolt_classtemplate.rst
:template: graphbolt_classtemplate.rst
OnDiskDataset
MiniBatchTransformer
BuiltinDataset
NegativeSampler
FusedCSCSamplingGraph
UniformNegativeSampler
UniformNegativeSampler
SubgraphSampler
---------------
A subgraph sampler is for sampling subgraphs from a graph.
.. autosummary::
:toctree: ../../generated/
:nosignatures:
:template: graphbolt_classtemplate.rst
SubgraphSampler
SampledSubgraph
NeighborSampler
NeighborSampler
LayerNeighborSampler
LayerNeighborSampler
SampledSubgraphImpl
FusedSampledSubgraphImpl
FusedSampledSubgraphImpl
BasicFeatureStore
InSubgraphSampler
TorchBasedFeature
TorchBasedFeatureStore
GPUCachedFeature
FeatureFetcher
--------------
A feature fetcher is for fetching features from a feature store.