Load 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", deserializeCudaEngine returns nullptr, gets an enqueueV2 / IStreamReader deprecation warning, or wants to stream a .plan via IStreamReaderV2. Triggers: TensorRT C++ inference, load TensorRT plan C++, run .plan from C++, IRuntime example, deserializeCudaEngine, enqueueV3, enqueueV2 deprecated, setTensorAddress, getBindingIndex, IStreamReaderV2, libnvinfer C++. NOT for building engines (trt-onnx-quickstart), Python deploy, plugins, multi-GPU.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryEngineeringStars0
About this skill
Load 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", deserializeCudaEngine returns nullptr, gets an enqueueV2 / IStreamReader deprecation warning, or wants to stream a .plan via IStreamReaderV2. Triggers: TensorRT C++ inference, load TensorRT plan C++, run .plan from C++, IRuntime example, deserializeCudaEngine, enqueueV3, enqueueV2 deprecated, setTensorAddress, getBindingIndex, IStreamReaderV2, libnvinfer C++. NOT for building engines (trt-onnx-quickstart), Python deploy, plugins, multi-GPU.
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Load 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", deserializeCudaEngine returns nullptr, gets an enqueueV2 / IStreamReader deprecation warning, or wants to stream a .plan via IStreamReaderV2. Triggers: TensorRT C++ inference, load TensorRT plan C++, run .plan from C++, IRuntime example, deserializeCudaEngine, enqueueV3, enqueueV2 deprecated, setTensorAddress, getBindingIndex, IStreamReaderV2, libnvinfer C++. NOT for building engines (`trt-onnx-quickstart`), Python deploy, plugins, multi-GPU.
About this listing
Category
Engineering
Reported license
Apache-2.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI