Torch-sparse

Latest version: v0.6.18

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0.6.18

What's Changed
* Support sparse element-wise multiplication in `SparseTensor` via `sparse_mat1 * sparse_mat2` (https://github.com/rusty1s/pytorch_sparse/pull/323)
* Fix gradient computation in `to_symmetric` (https://github.com/rusty1s/pytorch_sparse/pull/327)
* Fix empty edge indices handling (https://github.com/rusty1s/pytorch_sparse/pull/332)
* Add `mps` Apple silicon GPU Acceleration support (https://github.com/rusty1s/pytorch_sparse/pull/335)
* Fix shape of `node_weight` in `metis` computation (https://github.com/rusty1s/pytorch_sparse/pull/342)
* Add PyTorch 2.1.0 support (https://github.com/rusty1s/pytorch_sparse/pull/344)

New Contributors
* AndreasBergmeister made their first contribution in https://github.com/rusty1s/pytorch_sparse/pull/323
* ezyang made their first contribution in https://github.com/rusty1s/pytorch_sparse/pull/325
* jamesmyatt made their first contribution in https://github.com/rusty1s/pytorch_sparse/pull/330
* AgarwalSaurav made their first contribution in https://github.com/rusty1s/pytorch_sparse/pull/331
* NripeshN made their first contribution in https://github.com/rusty1s/pytorch_sparse/pull/335

**Full Changelog**: https://github.com/rusty1s/pytorch_sparse/compare/0.6.17...0.6.18

0.6.17

* PyTorch 2.0 support (317)
* Integrated faster `index_sort` in case `pyg-lib` is installed as well (306)
* Added a `balance_edge` option to the METIS graph partitioning algorithm (309)
* Added `SparseTensor.to_torch_sparse_csc_tensor` functionality (319)

0.6.16

* Fix `spspmm` on newer CUDA versions/GPUs
* PyTorch 1.13 support
* `torch.bfloat16` support in `spmm`
* Use faster hash-map routine in CPP code paths

0.6.15

* Temporal sampling is now correctly performed in disjoint mode (267)
* Replace `std::unordered_map` with `phmap::flat_hash_map` for faster sampling (266)
* Neighborhood sampling on heterogeneous graphs is now fully-deterministic (265)

0.6.14

* Internal C++ method for sampling neighbors based on temporal constraints (202, 225, 226)
* Sampling operators now respect `torch.manual_seed` (217)

0.6.13

* `SparseTensor`: `__eq__` functionality
* `SparseTensor`: `add` functionality of two sparse matrices (177)
* `SparseTensor`: `to_torch_csr_tensor` and `from_torch_csr_tensor` functionality
* `SparseTensor`: Allow indexing via `np.array` (194)
* `SparseTensor`: Skip unnecessary assertions and enable non-blocking data transfers (195)
* Allow loading of CPU wheels in a PyTorch CUDA installation

**PyTorch 1.10 is now required.**

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