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TensorRT
TensorRT enthält 2 gesammelte Skills von pytorch, mit Repository-Berufsabdeckung und Skill-Detailseiten auf SkillsMP.
Skills in diesem Repository
Analyze torch-tensorrt local test results and drive failures to a fix. Use when the user pastes a test report / summary, asks why tests failed, asks to triage or fix failing tests, or mentions the JUnit/test-summary output from `just tests-report` / `just test-summary`. Covers where the JUnit XMLs live, how to read the consolidated report, how to reproduce a single failure, and how to categorize (real bug vs torch-API change vs OOM/skip vs flake).
Build torch-tensorrt locally — install/pin the matching PyTorch nightly, drive Bazel through setup.py, do a clean rebuild after libtorch ABI changes, and recover from common build failures (undefined symbol, stale _C.so, libtorchtrt.so missing). Invoke whenever the user asks to build, rebuild, install editable, or upgrade the torch nightly; or when an import fails with an undefined-symbol error tying torch_tensorrt to libtorch.