Add Apple Silicon MPS support to predict.py - #24
Open
javahedi wants to merge 2 commits into
Open
Conversation
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
1 participant
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Summary
This PR adds automatic PyTorch device selection to
predict.py, allowing TrackNetV3 inference to run on Apple Silicon using the MPS backend.The device is selected in the following order:
Hardcoded
.cuda()calls are replaced with.to(device)so the existing CUDA workflow remains supported while making inference portable to macOS/Apple Silicon.Motivation
The current prediction script assumes an NVIDIA CUDA environment, which prevents it from running directly on Apple Silicon Macs.
This change keeps the existing behavior for CUDA users while enabling TrackNetV3 inference through PyTorch MPS.
Testing
python -m py_compile predict.py.cuda()calls inpredict.py