GitLab

updated resampling module to handle corner cases where the input signal needs to be extended towards the pole

Adding FilterBasis datastructure to contain information about the type of basis used in disco convolution

adding local SNO architecture and updating trraining script for SWE prediction with powerspectrum computation

This small fix removes the maximum version number requirement of torch harmonics

* safeguarding all custom CUDA and C++ routines via the _cuda_extension_available flag

* bumping up version number

* added analytic gradients to the gradient_analysis notebook

* fixing sht unittest to not check the roundtrip gradient but sht and isht individually

* Updated changelog

* changing distributeds SHT to use dim=-3 as the channel dimension for distributed transpose

* Fixed formatting in tests

* Adding bash script for running test suite

* Replaced asserts regarding number of dimensions in tensor with checks

* Adding spherical upsampling routine and example notebook for resampling

- doing manual type conversion in custom autograd
- fixing stride issues in backward pass by making some output tensors contiguous

* AMP hotfix

* Bumping up version to 0.7.1

* reworked the setup system to use pyproject.toml

* changed the way custom CUDA extension build flag is passed

* reworked the CI

* changed to source distribution only in the CI

* reverting deploy script

* moving setuptools install

* removing requirements

* bumping up version

* bumping up the torch-harmonics version to 0.7.0

* updating amp to new torch.amp
* using amp autocrats to FP32 for disco convolution kernels
* implemented reduce_scatter routines but disabled those because of memory fluctuations which can cause OOM on big networks

* missed one instance of python3

* fused multiplication of quadrature into multiplication of the Psi tensor

* Added quadrature change to changelog

* removing persistent quad weights tensor as it isn't needed anymore

* added pretty-prenting for convolution modules

* adjusting default value in convolution test

* removing unneccessary contiguous statements

* replacing reduce scatter with independent reduce and scatter