Comments (1)
Hi @RodneyPerhaps , thanks for your kind words :)
yes, backward propagation is supported as can be seen here.
from torch_sparse_solve.
Related Issues (12)
- speed? HOT 1
- Wired bugs: Process finished with exit code 139 (interrupted by signal 11: SIGSEGV) HOT 2
- Error: Failed building wheel for torch-sparse-solve HOT 1
- Install issue on google collab HOT 2
- [Question] Backward pass with respect to the sparse matrix - dense or sparse? HOT 2
- (very) incorrect solve for default test HOT 1
- Formulas in the backward HOT 2
- Avoiding the for loop in solve HOT 1
- Supporting pytorch_sparse HOT 1
- Avoiding dense matmult HOT 1
- Occur bugs when doing backward process. HOT 1
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from torch_sparse_solve.