Merge DiagMatrix class into SparseMatrix class, where the diagonal matrix is stored as a sparse matrix and inherits all the operators from sparse matrix.
Support converting DGLGraph to SparseMatrix.g.adj(self, etype=None, eweight_name=None) returns the sparse matrix representation of the DGL graph g on the edge type etype and edge weight eweight_name.
Enable zero-overhead conversion between Pytorch sparse tensors and SparseMatrix via dgl.sparse.to_torch_sparse_coo/csr/csc and dgl.sparse.from_torch_sparse.
SparseMatrix operators
Support element-wise multiplication on two sparse matrices with different sparsities, e.g., A * B.
Support element-wise division on two sparse matrices with the same sparsity, e.g., A / B.
Support broadcast operators on a sparse matrix and a 1-D tensor via dgl.sparse.broadcast_add/sub/mul/div.
Support column-wise softmax.
SparseMatrix examples
Example for Heterogeneous Graph Attention Networks (#5568 )
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Bumps dgl from 1.0.1 to 1.1.0.
Release notes
Sourced from dgl's releases.
... (truncated)
Commits
2e6112e
[Release] Modify release version to 1.1.0f635e2a
Polish Tutorial (#5645)1bd3688
[Tutorial] Add a small test for GAT exercise (#5644)24b7468
Update comment from 11.6 to 11.8. (#5641)5eff954
Change hat to bar. (#5640)d815a00
Turn on GPU. (#5639)50810a4
Update tutorial cu116 -> cu118. (#5638)f090e39
Update tutorial cu116 -> cu118. (#5637)852ddfb
Add gat exercise (#5635)d18d255
Update tutorial cu116 -> cu118. (#5636)Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
@dependabot rebase
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