trt-torch-quickstart
Installation
SKILL.md
Torch-TensorRT Quickstart
Convert a PyTorch nn.Module to a TensorRT engine using torch_tensorrt (the Torch-TensorRT frontend). Covers the AOT path (for production and C++ deploy) and the JIT path (for Python-only inference).
When to Use
| Scenario | Use this skill? |
|---|---|
PyTorch nn.Module; want a TensorRT engine without writing an ONNX intermediate |
Yes |
| Model uses ops that don't export cleanly to ONNX (custom autograd, dynamic control flow) | Yes |
| Want Torch-TensorRT's automatic fallback of unsupported subgraphs to PyTorch | Yes |
| Need a serialized engine for C++ deploy from a PyTorch source | Yes — use AOT path here, then trt-cpp-runtime-quickstart for the C++ load |
| Have a working ONNX file already | No — use trt-onnx-quickstart |
| LLM token generation (Llama, Mistral, Qwen text gen) | No — route to TensorRT-LLM |
Have a .plan file already and want to run it from C++ |
No — use trt-cpp-runtime-quickstart |
| Migrating an existing weakly-typed TRT network to strongly-typed | No — use trt-strong-typing-migration |