Releases: tum-pbs/PhiML
Releases · tum-pbs/PhiML
1.9.3
1.9.2
1.9.0
Highlights
convolve
now behaves like matrix multiplication, reducing dual dims of the kernelTensor @ 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 syntaxt->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 aliasesrotate
,cross
Shape
concatenation viaShape + Shape
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
1.7.4
1.7.2
1.7.1
1.7.0
New features
- Sparse SciPy and ML tensors can now be wrapped like regular tensors.
- Shorthand
shape & dual
to add corresponding dual dims - Added experimental compact sparse tensor
- Removing dims from a
Shape
can now be done using the-
operator. - Generic type conversion via
Shape.as_type()
.
Improvements
scatter()
is now more flexible withtreat_as_batch
argument.- Improvements to linear tracing. Improved rank deficiency detection. Linear solves will only use matrix_offset if confirmed by user.
minimum
andmaximum
can now be used withNone
values.- Stacked trees may now include
None
values. reshaped_native()
andreshaped_numpy()
now support()
/None
for singleton dims
1.6.0
Numerous fixes and various new features, see #6
Highlights
- JAX buffer management for variable-sized tensors
- JIT improvements and fixes
- Periodic pairwise_differences() and fixes
- Extrapolation by side with '+' and '-'
- Added
substeps
toiterate()
- Regularized linear solves for singular matrices
- Add
safe_mul()