v0.8.0

• Adding spherical attention and spherical neighborhood attention
• Custom CUDA kerneles for spherical neighborhood attention
• New datasets for segmentation and depth estimation on the sphere based on the 2D3DS dataset
• added new spherical architectures and corresponding baselines
  • S2 Transformer
  • S2 Segformer
  • S2 U-Net
• Reorganized examples folder, including new examples based on the 2d3ds dataset
• Added spherical loss functions to examples
• Added plotting module
• Updated docstrings

v0.7.4

• New filter basis normalization in DISCO convolutions
• More robust pre-computation of DISCO convolution tensor
• Reworked DISCO filter basis datastructure
• Support for new filter basis types
• Added Zernike polynomial basis on a disk
• Added Morlet wavelet basis functions on a spherical disk
• Cleaning up the SFNO example and adding new Local Spherical Neural Operator model
• Updated resampling module to extend input signal to the poles if needed
• Added slerp interpolation to the resampling module
• Added distributed resampling module

v0.7.3

• Changing default grid in all SHT routines to equiangular
• Hotfix to the numpy version requirements

v0.7.2

• Added resampling modules for convenience
• Changing behavior of distributed SHT to use dim=-3 as channel dimension
• Fixing SHT unittests to test SHT and ISHT individually, rather than the roundtrip
• Changing the way custom CUDA extensions are handled

v0.7.1

• Hotfix to AMP in SFNO example

v0.7.0

• CUDA-accelerated DISCO convolutions
• Updated DISCO convolutions to support even number of collocation points across the diameter
• Distributed DISCO convolutions
• Fused quadrature into multiplication with the Psi tensor to lower memory footprint
• Removed DISCO convolution in the plane to focus on the sphere
• Updated unit tests which now include tests for the distributed convolutions

v0.6.5

• Discrete-continuous (DISCO) convolutions on the sphere and in two dimensions
• DISCO supports isotropic and anisotropic kernel functions parameterized as hat functions
• Supports regular and transpose convolutions
• Experimental accelerated spherical DISCO convolutions on GPU via Triton Kernel
• Unittests for DISCO convolutions in tests/test_convolution.py

v0.6.4

• reworking distributed to allow for uneven split tensors, effectively removing the necessity of padding the transformed tensors
• distributed SHT tests are now using unittest. Test extended to vector SHT versions. Tests are defined in torch_harmonics/distributed/distributed_tests.py
• base pytorch container version bumped up to 23.11 in Dockerfile

v0.6.3

• Updated SFNO example
• Fixes NCCL issues with distributed SHT
• other bugixes

v0.6.2

• Adding github CI
• Changed SHT modules to convert dtype dynamically when computing the SHT/ISHT
• Bugfixes to fix importing examples