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2 changes: 1 addition & 1 deletion _config.yml
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ plugins:
- jekyll-redirect-from
kramdown:
parse_block_html: true
toc_levels: '2'
toc_levels: [2, 3, 4]
logo: '/images/ONNX-Runtime-logo.svg'
aux_links:
'ONNX Runtime':
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76 changes: 61 additions & 15 deletions docs/build/eps.md
Original file line number Diff line number Diff line change
Expand Up @@ -161,6 +161,65 @@ Dockerfile instructions are available [here](https://github.com/microsoft/onnxru

---

## NVIDIA TensorRT RTX

See more information on the TensorRT RTX Execution Provider [here](../execution-providers/TensorRTRTX-ExecutionProvider.md).

### Minimum requirements

| ONNX Runtime | TensorRT-RTX | CUDA Toolkit |
| :----------- | :----------- | :------------- |
| main branch | 1.1 | 12.9 |
| 1.23 | 1.1 | 12.9 |
| 1.22 | 1.0 | 12.8 |

TensorRT RTX EP supports RTX GPUs based on Ampere (GeForce RTX 30xx) and later architectures with minimum recommended NVIDIA driver version 555.85.

### Pre-requisites
* Install git, cmake, Python 3.12
* Install latest [NVIDIA driver](https://www.nvidia.com/en-us/drivers/)
* Install [CUDA toolkit 12.9](https://developer.nvidia.com/cuda-12-9-1-download-archive)
* Install [TensorRT RTX](https://docs.nvidia.com/deeplearning/tensorrt-rtx/latest/installing-tensorrt-rtx/installing.html)
* For Windows only, install [Visual Studio](https://visualstudio.microsoft.com/downloads/)
* Set TensorRT-RTX dlls in `PATH` or put it in same folder as application exe


```sh
git clone https://github.com/microsoft/onnxruntime.git
cd onnxruntime
```

### Windows

```powershell
.\build.bat --config Release --build_dir build --parallel --use_nv_tensorrt_rtx --tensorrt_rtx_home "path\to\tensorrt-rtx" --cuda_home "path\to\cuda\home" --cmake_generator "Visual Studio 17 2022" --build_shared_lib --skip_tests --build --update --use_vcpkg
```

### Linux

```sh
./build.sh --config Release --build_dir build --parallel --use_nv_tensorrt_rtx --tensorrt_rtx_home "path/to/tensorrt-rtx" --cuda_home "path/to/cuda/home" --build_shared_lib --skip_tests --build --update
```

### Run unit test
```powershell
.\build\Release\Release\onnxruntime_test_all.exe --gtest_filter=*NvExecutionProviderTest.*
```

### Python wheel

```powershell
# build the python wheel
.\build.bat --config Release --build_dir build --parallel --use_nv_tensorrt_rtx --tensorrt_rtx_home "path\to\tensorrt-rtx" --cuda_home "path\to\cuda\home" --cmake_generator "Visual Studio 17 2022" --build_shared_lib --skip_tests --build_wheel

# install
pip install "build\Release\Release\dist\onnxruntime-1.23.0-cp312-cp312-win_amd64.whl"
```

> NOTE: TensorRT-RTX .dll or .so are in `PATH` or in the same folder as the application

---

## NVIDIA Jetson TX1/TX2/Nano/Xavier/Orin

### Build Instructions
Expand Down Expand Up @@ -235,20 +294,7 @@ These instructions are for the latest [JetPack SDK](https://developer.nvidia.com

* For a portion of Jetson devices like the Xavier series, higher power mode involves more cores (up to 6) to compute but it consumes more resource when building ONNX Runtime. Set `--parallel 1` in the build command if OOM happens and system is hanging.

## TensorRT-RTX

See more information on the NV TensorRT RTX Execution Provider [here](../execution-providers/TensorRTRTX-ExecutionProvider.md).

### Prerequisites
{: .no_toc }

* Follow [instructions for CUDA execution provider](#cuda) to install CUDA and setup environment variables.
* Intall TensorRT for RTX from nvidia.com (TODO: add link when available)

### Build Instructions
{: .no_toc }
`build.bat --config Release --parallel 32 --build_dir _build --build_shared_lib --use_nv_tensorrt_rtx --tensorrt_home "C:\dev\TensorRT-RTX-1.1.0.3" --cuda_home "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.9" --cmake_generator "Visual Studio 17 2022" --use_vcpkg`
Replace the --tensorrt_home and --cuda_home with correct paths to CUDA and TensorRT-RTX installations.
---

## oneDNN

Expand Down Expand Up @@ -849,4 +895,4 @@ build.bat --config <Release|Debug|RelWithDebInfo> --build_shared_lib --build_whe

```bash
./build.sh --config <Release|Debug|RelWithDebInfo> --build_shared_lib --build_wheel --use_azure
```
```
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