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ci: upgrade apache-tvm-ffi version in ci containers#1788

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yzh119 merged 1 commit intoflashinfer-ai:mainfrom
yzh119:upgrade-apache-tvm-ffi
Sep 26, 2025
Merged

ci: upgrade apache-tvm-ffi version in ci containers#1788
yzh119 merged 1 commit intoflashinfer-ai:mainfrom
yzh119:upgrade-apache-tvm-ffi

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@yzh119 yzh119 commented Sep 26, 2025

📌 Description

Incorporate changes in apache/tvm-ffi@eb5492a to fix the CI errors in https://ci.tlcpack.ai/blue/organizations/jenkins/flashinfer-ci/detail/PR-1641/95/pipeline

🔍 Related Issues

#1641

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Reviewer Notes

cc @nvmbreughe @cyx-6 @tqchen

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Summary of Changes

Hello @yzh119, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on enhancing the stability of the continuous integration pipeline by updating a critical dependency. The change ensures that the build process can proceed without encountering known errors related to an outdated package version, thereby maintaining a reliable development environment.

Highlights

  • Dependency Upgrade: The apache-tvm-ffi package has been upgraded to version 0.1.0b8 in the CI containers.
  • CI Stability: This upgrade is intended to resolve existing continuous integration failures, specifically addressing issues seen in PR-1641.
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Code Review

This pull request updates the apache-tvm-ffi package version in the CI container installation script, pinning it to 0.1.0b8. This is a good change that improves the reproducibility of the CI environment. I have added one suggestion to consider moving all Python dependencies to a requirements.txt file to further enhance maintainability and ensure all dependencies are pinned, which is a best practice for CI environments.

pip3 install torch --index-url https://download.pytorch.org/whl/${CUDA_VERSION}
pip3 install requests ninja pytest numpy scipy build nvidia-ml-py cuda-python einops nvidia-nvshmem-cu12
pip3 install 'apache-tvm-ffi>=0.1.0b6'
pip3 install 'apache-tvm-ffi==0.1.0b8'
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medium

Pinning the apache-tvm-ffi version is a great step for ensuring reproducible builds. To improve maintainability and consistency across all dependencies, consider moving all Python packages into a requirements.txt file. This centralizes dependency management, makes it clear which versions are used, and prevents potential issues from unpinned packages in the future. You could then replace the multiple pip3 install calls with a single pip3 install -r path/to/requirements.txt.

@yzh119 yzh119 merged commit dada75b into flashinfer-ai:main Sep 26, 2025
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