1.8.0
Highlights
- NumPy 2 compatibility
Tensor.numpy()
and.native()
now support dim packingwrap()
andtensor()
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 aliaseslength
,rand
,randn
. - Shapes can now be stacked using
stack
unpack_dim
can now be used with non-uniform targets