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License: Apache License 2.0
This project forked from google-research/smore
License: Apache License 2.0
The overall goal is to fit SMORE
into the PyG interface, and to re-use as much of PyG's functionality as possible. This involves:
InMemoryDataset
SparseEmbedding
functionality with asychronous access directly in PyG (can be later used for integration with GNNAutoScale
as well)MessagePassing
whenever possibletorch_geometric.utils
or torch_geometric.metrics
In general, I'm in favor of storing KGs as pure PyTorch tensors, and utilize the torch.extension
package for C++/CUDA integration (similar to how torch-scatter
and torch-sparse
works). This should also allow us to have @torch.jit.script
support for C++ extensions.
We can store KGs in CSR representation based on head type. Relations can be sorted based on relation id inside each head id and can be then effectively queried via binary search.
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