Add GPU Wavelet transform support.#338
Merged
paquiteau merged 6 commits intoCEA-COSMIC:masterfrom Feb 16, 2024
Merged
Conversation
Ideally we want to have such support everywhere.
chaithyagr
approved these changes
Feb 5, 2024
Contributor
chaithyagr
left a comment
There was a problem hiding this comment.
LGTM except minor stuff. Also, can we add a test? I know it cant work on CPU, but for now with skip so that we can launch it later when we have local clusters
Contributor
|
This is failing due to pipeline issues? |
Contributor
|
Thank you, LGTM. If you have time, do consider writing an example in pysap-mri using this! (All GPU reconstruction workflow) |
5 tasks
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This PR add a new optional library for computing wavelet on GPU, using the pytorch wavelet toolbox. In order to make things easier, a wrapper using cupy is also provided.
The current support for GPU array (e.g. using cupy instead of numpy) is not possible everywhere yet. I propose that we tackle each operators/group of operator separatly. A possible way of doing is shown for
SparseThresholdbut maybe a more generic way is possible (using a decorator maybe?).