All notable changes to this project will be documented in this file. The format is based on Keep a Changelog.
- Added support for
follow_batchfor lists or dictionaries of tensors (#4837) - Added
Data.validate()andHeteroData.validate()functionality (#4885) - Added
LinkNeighborLoadersupport toLightningDataModule(#4868) - Added
predict()support to theLightningNodeDatamodule (#4884) - Added
time_attrargument toLinkNeighborLoader(#4877) - Added a
filter_per_workerargument to data loaders to allow filtering of data within sub-processes (#4873) - Added a
NeighborLoaderbenchmark script (#4815) - Added support for
FeatureStoreandGraphStoreinNeighborLoader(#4817, #4851, #4854, #4856, #4857, #4882, #4883) - Added a
normalizeparameter todense_diff_pool(#4847) - Added
size=Noneexplanation to jittableMessagePassingmodules in the documentation (#4850) - Added documentation to the
DataLoaderIteratorclass (#4838) - Added
GraphStoresupport toDataandHeteroData(#4816) - Added
FeatureStoresupport toDataandHeteroData(#4807, #4853) - Added support for dense aggregations in
global_*_pool(#4827) - Added Python version requirement (#4825)
- Added TorchScript support to
JumpingKnowledgemodule (#4805) - Added a
max_sampleargument toAddMetaPathsin order to tackle very dense metapath edges (#4750) - Test
HANConvwith empty tensors (#4756, #4841) - Added the
biasvector to theGCNmodel definition in the "Create Message Passing Networks" tutorial (#4755) - Added
transforms.RootedSubgraphinterface with two implementations:RootedEgoNetsandRootedRWSubgraph(#3926) - Added
ptrvectors forfollow_batchattributes withinBatch.from_data_list(#4723) - Added
torch_geometric.nn.aggrpackage (#4687, #4721, #4731, #4762, #4749, #4779, #4863, #4865, #4866, #4872) - Added the
DimeNet++model (#4432, #4699, #4700, #4800) - Added an example of using PyG with PyTorch Ignite (#4487)
- Added
GroupAddRevmodule with support for reducing training GPU memory (#4671, #4701, #4715, #4730) - Added benchmarks via
wandb(#4656, #4672, #4676) - Added
unbatchfunctionality (#4628) - Confirm that
to_hetero()works with custom functions, e.g.,dropout_adj(4653) - Added the
MLP.plain_last=Falseoption (4652) - Added a check in
HeteroConvandto_hetero()to ensure thatMessagePassing.add_self_loopsis disabled (4647) - Added
HeteroData.subgraph()support (#4635) - Added the
AQSOLdataset (#4626) - Added
HeteroData.node_items()andHeteroData.edge_items()functionality (#4644) - Added PyTorch Lightning support in GraphGym (#4531, #4689, #4843)
- Added support for returning embeddings in
MLPmodels (#4625) - Added faster initialization of
NeighborLoaderin case edge indices are already sorted (viais_sorted=True) (#4620, #4702) - Added
AddPositionalEncodingtransform (#4521) - Added
HeteroData.is_undirected()support (#4604) - Added the
GeniusandWikidatasets tonn.datasets.LINKXDataset(#4570, #4600) - Added
nn.glob.GlobalPoolingmodule with support for multiple aggregations (#4582) - Added support for graph-level outputs in
to_hetero(#4582) - Added
CHANGELOG.md(#4581)
- Removed unnecssary inclusion of self-loops when sampling negative edges (#4880)
- Fixed
InMemoryDatasetinferring wronglenfor lists of tensors (#4837) - Fixed
Batch.separatewhen using it for lists of tensors (#4837) - Correct docstring for SAGEConv (#4852)
- Fixed a bug in
TUDatasetwherepre_filterwas not applied wheneverpre_transformwas present - Renamed
RandomTranslatetoRandomJitter- the usage ofRandomTranslateis now deprecated (#4828) - Do not allow accessing edge types in
HeteroDatawith two node types when there exists multiple relations between these types (#4782) - Allow
edge_type == rev_edge_typeargument inRandomLinkSplit(#4757) - Fixed a numerical instability in the
GeneralConvandneighbor_sampletests (#4754) - Fixed a bug in
HANConvin which destination node features rather than source node features were propagated (#4753) - Fixed versions of
checkoutandsetup-pythonin CI (#4751) - Fixed
protobufversion (#4719) - Fixed the ranking protocol bug in the RGCN link prediction example (#4688)
- Math support in Markdown (#4683)
- Allow for
setterproperties inData(#4682, #4686) - Allow for optional
edge_weightinGCN2Conv(#4670) - Fixed the interplay between
TUDatasetandpre_transformthat modify node features (#4669) - Make use of the
pyg_sphinx_themedocumentation template (#4664, #4667) - Refactored reading molecular positions from sdf file for qm9 datasets (4654)
- Fixed
MLP.jittable()bug in casereturn_emb=True(#4645, #4648) - The generated node features of
StochasticBlockModelDatasetare now ordered with respect to their labels (#4617) - Fixed typos in the documentation (#4616, #4824, #4895)
- The
biasargument inTAGConvis now actually applied (#4597) - Fixed subclass behaviour of
processanddownloadinDatsaet(#4586) - Fixed filtering of attributes for loaders in case
__cat_dim__ != 0(#4629)