Run unit tests and simulated sessions for GPU tuning scripts.
npx skills add https://github.com/LancerLab/croqtile-tuner --skill testing-lancerlab
Please help me install this Agent Skill. Skill: testing Source: https://github.com/LancerLab/croqtile-tuner/tree/main/testing Command: npx skills add https://github.com/LancerLab/croqtile-tuner --skill testing-lancerlab
This Skill enables comprehensive testing of GPU tuning scripts and tools, ensuring reliable and error-free operation.
next_iter.sh, store_round.sh, and profile_extract.sh.Run all tests from the repo root to verify that the entire testing pipeline and associated scripts operate correctly.
High-intent search queries and answers about installing and using this skill.
Run all unit tests from the repository root to validate individual GPU tuning scripts like next_iter.sh and store_round.sh, ensuring each component functions correctly before integration.
Yes, you can validate GPU tuning workflows without hardware by using mock tools and shell scripts to simulate full end-to-end session cycles and mimic environment dependencies.
Automate regression testing for tuning workflows by integrating this Skill into continuous testing pipelines, running simulated sessions and unit tests whenever script changes occur to prevent regressions.
No, you do not need actual GPU hardware to run end-to-end validation. The Skill relies on mock tools and shell scripts to mimic hardware and environment dependencies for simulating full session cycles.
You can validate specific GPU tuning components including next_iter.sh, store_round.sh, and profile_extract.sh through unit tests, and simulate full tuning session cycles through end-to-end validation.
Regressions in GPU tuning scripts occur when changes introduce errors. Integrate automated unit tests and simulated sessions into continuous testing pipelines to catch these regressions early before deployment.
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