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Releases: NVIDIA/torch-harmonics

v0.7.4

14 Jan 16:21
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  • 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

17 Dec 00:12
837335f
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  • Changing default grid in all SHT routines to equiangular
  • Hotfix to the numpy version requirements

v0.7.2

01 Oct 16:34
663bea1
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  • 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

27 Aug 21:47
5d7e9b0
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  • Hotfix to AMP in SFNO example

v0.7.0

27 Aug 16:49
1bfda53
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  • 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

30 Jan 14:08
54502a1
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  • 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

07 Dec 12:47
eab72f0
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  • 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

25 Nov 17:28
13aa492
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  • Updated SFNO example
  • Fixes NCCL issues with distributed SHT
  • other bugixes

v0.6.2

08 Aug 09:47
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  • Adding github CI
  • Changed SHT modules to convert dtype dynamically when computing the SHT/ISHT
  • Bugfixes to fix importing examples

v0.6.1

08 Jun 14:36
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  • Minor bugfixes to export SFNO code
  • Readme should now render correctly in PyPI