Phiml

Bug fixes plus

* Performance optimization for `stack()`
* experimental save/load
* `at_min, at_max` now support sparse matrices

Various smaller bug fixes, `map` now exposes `expand_results`.

**Highlights**

* `convolve` now behaves like matrix multiplication, reducing dual dims of the kernel
* `Tensor Tensor` can now be used to reduce channel dims in the absence of dual dims
* Improved support for shape spec strings, `concat` now supports packing using the syntax `t->name:t`
* Multi-dimensional `cumulative_sum`
* Improved support for non-uniform and sparse tensors
* New functions `d2s`, `contains`, `count_occurrences`, `Tensor.map()`, `ravel_index` and aliases `rotate`, `cross`
* `Shape` concatenation via `Shape + Shape`

**Highlights**

* NumPy 2 compatibility
* `Tensor.numpy()` and `.native()` now support dim packing
* `wrap()` and `tensor()` now support shape spec strings, e.g. `'example:b,(x,y,z)'`
* Compact sparse tensors can now be created using `sparse_tensor` (experimental)
* Support for SVD and eigenvalues
* Shorthand notation `dim in Tensor`
* Various improvements for sparse tensors
* Support save/load on Stax nets
* Added `tensor.T` to transpose a tensor. This switches primal/dual dims.
* Added functions `ravel_index`, `d2i` and aliases `length`, `rand`, `randn`.
* Shapes can now be stacked using `stack`
* `unpack_dim` can now be used with non-uniform targets