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setup-trtmc-environment

Prepare a TensorRT-Model-Connect development or validation environment from a fresh checkout on a host without a known working setup.

Quellinformationen

Repository
NVIDIA/TensorRT-Model-Connect
Letzte Quellaktivität
7. September 2026 um 07:41
Erkannte Sprache von SKILL.md
Englisch
Sterne
273
Forks
71

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
setup-trtmc-environment
description
Prepare a TensorRT-Model-Connect development or validation environment from a fresh checkout on a host without a known working setup.
# Set Up the Environment Start from the checkout and current repository documentation, not a remembered machine or container name. 1. Resolve the repository root and read `website/docs/getting-started/source-build.md`, `Dockerfile`, and `apps/devtoolkit/README.md`. 2. Inspect host architecture, available disk, Docker access, GPU visibility, driver, and compute capability only as needed for the requested work. 3. Prefer the existing `apps/devtoolkit` API for a checkout-owned environment. Use its Docker path for the supported development image or its local path with an explicit existing Python interpreter. 4. Select one family when model work is requested. Install only that family's optional `families/<family>/requirements.txt`; a missing file means no family package step. 5. Verify the checkout mount, Python import, TensorRT import, GPU visibility, runtime root, and requested native target before starting the real task. Do not reuse, replace, or remove an unrelated container. Do not install GPU drivers, reconfigure the container runtime, or change runner settings without separate authorization. Stop and explain the unsupported host boundary when the documented paths do not apply. Report environment preparation separately from compilation, tests, model correctness, performance, and deployment qualification.
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