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chilo-ms merged 1 commit into from
Sep 18, 2025
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[TRT RTX EP] update documentation #26082

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17 changes: 12 additions & 5 deletions docs/execution-providers/TensorRTRTX-ExecutionProvider.md
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Expand Up @@ -135,18 +135,25 @@ For a practical example of usage for EP context, please refer to:
* EP context samples
* EP context [unit tests](https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/test/providers/nv_tensorrt_rtx/nv_ep_context_test.cc)

There are two other ways to quick generate an EP context model:

**ONNXRuntime Perf Test**
ONNXRuntime Perf Test can also be used to quick generate an EP context model:

```sh
onnxruntime_perf_test.exe -e nvtensorrtrtx -I -r 1 --compile_ep_context --compile_model_path "/path/to/model_ctx.onnx" "/path/to/model.onnx"
```

**Python Script**
**Python**

```sh
python tools/python/compile_ep_context_model.py -i "path/to/model.onnx" -o "/path/to/model_ctx.onnx"
```py
import onnxruntime as ort

input_path = "/path/to/model.onnx"
output_path = "/path/to/model_ctx.onnx"

session_options = ort.SessionOptions()
session_options.add_provider("NvTensorRTRTXExecutionProvider", {})
model_compiler = ort.ModelCompiler(session_options, input_path)
model_compiler.compile_to_file(output_path)
```

**NVIDIA recommended settings**
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