Torch-cluster

* Fix backward compatibility issue with PyTorch < 1.12
* Remove `torch.jit.script` conversion of functions on module import

What's Changed
* Add `batch_size` argument for `fps`, `knn`, `radius` functions (https://github.com/rusty1s/pytorch_cluster/pull/175)
* Extend FPS with an extra `ptr` argument https://github.com/rusty1s/pytorch_cluster/pull/180)
* Add PyTorch 2.1.0 support (https://github.com/rusty1s/pytorch_cluster/pull/191)

New Contributors
* piotrchmiel made their first contribution in https://github.com/rusty1s/pytorch_cluster/pull/175
* cimadure made their first contribution in https://github.com/rusty1s/pytorch_cluster/pull/179
* dsciebu made their first contribution in https://github.com/rusty1s/pytorch_cluster/pull/180
* AgarwalSaurav made their first contribution in https://github.com/rusty1s/pytorch_cluster/pull/188

**Full Changelog**: https://github.com/rusty1s/pytorch_cluster/compare/1.6.1...1.6.2

* Added support for PyTorch 2.0
* Added support for return the indices of sampled edges in `random_walk` (139)
* Added `bf16` support for `knn`, `radius` and `graclus` (144)
* Add safety checks on `batch` layout in `nearest` (168)

* Improve calculation of `num_nodes` in `random_walk` (in case `num_nodes=None`) (112)
* Fix `knn`/`radius` calculation for batches with zero-point examples
* Heavily improved efficiency of `knn`/`radius` calculation
* Half-precision support (119)

* Reduced the size of shared library files
* CUDA wheels can now also operate on CPU-only devices
* Added parallelization strategies for CPU functionalities
* `fps` can now take in different ratios across different batched point sets, *i.e.* `ratio` can now be a `torch.Tensor`
* Fixed a bug in which `radius` computed slightly different results across CPU and CUDA versions

* PyTorch 1.7 wheels
* `random_walk` now supports `q != 1` and `p != 1` via rejection sampling