Fix #153: Allow CPU fallback in forward_projection and add_noise - #189
Open
Paramveersingh-S wants to merge 1 commit into
Open
Fix #153: Allow CPU fallback in forward_projection and add_noise#189Paramveersingh-S wants to merge 1 commit into
Paramveersingh-S wants to merge 1 commit into
Conversation
Member
|
Im not sure if your AI agent got confused here, as I think this breaks a feature: selecting the current device. Users may have chosen a specific device, if we set it to just cuda, pythorch may chose a different one. This is bad for shared computers or when the user has specifically chosen one gpu |
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
2 participants
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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 replaces the hardcoded usage of torch.cuda.current_device() in forward_projection and _sinogram_add_noise with a dynamic device check (torch.device("cuda" if torch.cuda.is_available() else "cpu")). In addition, proj.cuda(dev) was refactored to use .to(dev) to prevent runtime crashes when running on a CPU-only host for local prototyping.