fix(deps): Resolve torch installation issues on macOS Intel #1018
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
The dependency specification for 'torch' was failing on macOS machines running on the Intel (x86_64) architecture when using UV. The generic constraint 'torch>=2.0.0' was leading to UV attempting to download the latest available version, which often lacks pre-built wheels for older architectures or specific macOS versions. This fix updates the 'torch' dependency to use an **environment marker** to explicitly pin a known-compatible version for the targeted 'darwin'/'x86_64' environment defined in [tool.uv]. This ensures a successful sync by forcing the installation of a supported wheel.
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Outdated suggestions cannot be applied.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.
The dependency 'torch>=2.0.0' was leading to installation failures on macOS Intel (x86_64). This PR pins a known-compatible version using an environment marker in pyproject.toml to ensure successful syncing.