All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
0.0.5 - 2024-11-04
This release adds a minor improvement of the structured matrix sub-module.
.shape
property of aStructuredMatrix
(PR)
0.0.4 - 2024-07-03
This release adds a new interface function to SINGD
's structured matrix
sub-module. This is a useful addition for our
SIRFShampoo
optimizer. The SINGD
optimizer is not affected by this feature.
- Method to extract a structured matrix from
X @ X.T
(PR)
0.0.3 - 2024-06-24
This release requires torch>=2.2.0
and ships internal refactorings to update
newly supported operations in half precision.
- Functionality to compute the Frobenius norm of a structured matrix (interface PR, efficient implementation PR)
- Update
.bib
entry to ICML 2024 (PR)
- Use
torch>=2.2.0
and update its newly added support formatmul
,conv1d
, andeinsum
in half precision on CPU (PR)
No bug fixes
0.0.2 - 2023-12-11
This release adds support for neural networks with in-place activations and also comes with performance improvements for convolutions, as well as improvements regarding numerical stability in half precision.
New features:
- Support
Conv2d
layers withdilation != 1
(PR) - Support neural networks with inplace activation functions (PR)
Performance improvements:
- Speed up input processing for
Conv2d
withgroups != 1
(PR) - Speed up computation of averaged patches for KFAC-reduce
(
kfac_approx='reduce'
) inConv2d
using the tensor network approach of Dangel, 2023 (PR)
- Move un-scaling of
H_C
into the update step to improve numerical stability when using half precision + gradient scaling (PR)
No deprecations
No bug fixes
0.0.1 - 2023-10-31
Initial release