Torchkbnufft

This release supports the latest version of PyTorch (1.13.0) and adds a new build and versioning system. A list of some work on the current release:

- Changed default normalization for Toeplitz to `"ortho"` (PR 43)
- From ckolbPTB, fixed size of weights in `calc_toeplitz_kernel` (PR 47)
- From ckolbPTB, allowed use of single smap for batches for Toeplitz NUFFT (PR 48)
- Updates for internal type system (PR 77)
- Updates for package dependencies and build system (PR 78, 79)

- Fixes Toeplitz NUFFT scaling issue (PR 39)
- Updates for requirements to current PyTorch (PR 40)

Fixes formatting for a reference on the main documentation page.

This pure-documentation release fixes an issue with how documentation headers were rendered on the ReadTheDocs website. See PR 29.

This updates `torchkbnufft` for PyTorch version 1.8. It uses a new version of `index_add` that operates natively on complex tensors. The update also fixes a performance regression that arose due to thread management as identified in Issue 25.

Most changes came from PR 27, which has the below list of modifications:

- Update `requirements.txt` and `dev-requirements.txt` to latest packages.
- Remove `calc_split_sizes` - we can now use `tensor_split`.
- Removed some calls to tensor attributes - these can be expensive.
- Removal of `kwarg` usage for some `torch.jit.script` functions - these can behave strangely with scripted functions.
- Removal of `index_put` for accumulation. We now only use `index_add`.

This adds support for a new batched NUFFT, which is substantially faster than using a Python for loop over the batch dimension when applying a NUFFT with many small k-space trajectories. It also updates the documentation and includes a new page for performance tips. See PR 24 and Issue 24 for details and testing.