Trt Onnx Quickstart
NVIDIA/trt-samples-for-hackathon-cn/.claude/skills/trt-onnx-quickstartai-mlOfficial
Official Provider SkillView repo
Build and verify a TensorRT engine from a Hugging Face model ID or ONNX file, with numerical parity checked against ONNX Runtime. Use when the user imports a non-LLM model to TensorRT, needs a verified engine from ONNX, hits trtexec "unsupported operator", must verify the engine matches ONNX numerically, debugs a polygraphy parity failure (large max abs diff at FP16), or configures multi-input dynamic shapes. Triggers: convert ONNX to TensorRT, Hugging Face to TensorRT, trtexec onnx, trtexec uns
Files1 files
SKILL.md344 lines
Loading editor…
Install
RecommendedOne command — your agent picks it up automatically.
Select an AI agent above to see the install command.
or
Manual Install
More stepsDownload the file and paste it into your agent's system prompt.
Skill details
Versionv1.0.0
AuthorNVIDIA
Categoryai-ml
Skill IDNVIDIA/trt-samples-for-hackathon-cn/.claude/skills/trt-onnx-quickstart
Related skills
Trt Cpp Runtime QuickstartLoad and run a TensorRT engine (.plan / .engine) from C++ using the TensorRT 11 / 10.x **modern Runtime API**, avoiding the deprecated TRT 8.x binding-index APIs that older guidance still promotes. Use whenever the user asks about loading or running a TensorRT .plan/.engine from C++, even on "minimal example" requests — without this skill the default reply uses deprecated enqueueV2-style code. Also use when the user hits "Engine plan file is generated on an incompatible device", deserializeCudaETrt Perf AnalysisValidate and analyze TensorRT performance data from paired layer-info JSON and profile/latency JSON files. Use when asked to inspect TensorRT, TRT, torch-tensorrt, or ONNX-TensorRT perf reports, verify that layer/profile JSON files are valid and from the same model, infer basic model information, find likely fusion or latency optimization opportunities, and produce a concise Markdown performance report or structured JSON data.Trt Strong Typing MigrationMigrate a TensorRT build from weak typing (deprecated 10.12, removed 11.0) to strong typing — across Python INetworkDefinition builders, the trtexec CLI, and C++ builder code. Use when a TRT 11 upgrade breaks a weakly-typed build. Triggers: weakly typed to strongly typed, kSTRONGLY_TYPED, weak typing deprecated, kFP16/kINT8 removed, setPrecision rejected, setComputePrecision deprecated, do I still need --stronglyTyped, how to add the kSTRONGLY_TYPED flag, ModelOpt autocast, INT8 on TRT 11. NOT fTrt Torch QuickstartCompile a PyTorch model to a TensorRT engine via Torch-TensorRT — AOT or JIT — under the new strong-typing default. Use when the user compiles PyTorch to TensorRT without ONNX, hits "enabled_precisions should not be used when use_explicit_typing=True", sees Dynamo graph breaks or PyTorch fallback, debugs ABI errors at import torch_tensorrt, or needs the compatible torch / torch_tensorrt / tensorrt-cu13 version pins for TensorRT 11. Triggers: torch_tensorrt, torch_tensorrt.dynamo.compile, torch.cNemoclaw Maintainer Cross Issue SweepScans other open issues to find ones a given PR may also fix or accidentally break. Outputs adjacent-fix opportunities and contradiction risks with file:line evidence. Use when reviewing a PR to discover bundling opportunities or downstream impact across the issue queue.Nemoclaw Maintainer EveningRuns the end-of-day maintainer handoff for NemoClaw. Checks version target progress, records stragglers for an automatic post-tag bump, generates a QA handoff summary, and cuts the release tag. Use at the end of the workday. Trigger keywords - evening, end of day, EOD, wrap up, ship it, cut tag, handoff, done for the day.