mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-07-14 18:12:05 +00:00
d4497b9ecd
### Description - Update EP ordering and distinguish between MS-maintained and community-maintained EPs - Update CUDA version table for v1.13 - Staged preview: https://faxu.github.io/onnxruntime/docs/execution-providers/
71 lines
1.5 KiB
Markdown
71 lines
1.5 KiB
Markdown
---
|
|
title: AMD - ROCm
|
|
description: Instructions to execute ONNX Runtime with the AMD ROCm execution provider
|
|
parent: Execution Providers
|
|
nav_order: 10
|
|
redirect_from: /docs/reference/execution-providers/ROCm-ExecutionProvider
|
|
---
|
|
|
|
# ROCm Execution Provider
|
|
{: .no_toc }
|
|
|
|
The ROCm Execution Provider enables hardware accelerated computation on AMD ROCm-enabled GPUs.
|
|
|
|
## Contents
|
|
{: .no_toc }
|
|
|
|
* TOC placeholder
|
|
{:toc}
|
|
|
|
## Install
|
|
|
|
Pre-built binaries of ONNX Runtime with ROCm EP are published for most language bindings. Please reference [Install ORT](../install).
|
|
|
|
## Requirements
|
|
|
|
|
|
|ONNX Runtime|ROCm|
|
|
|---|---|
|
|
|main|5.2.3|
|
|
|1.12|5.2.3|
|
|
|1.12|5.2|
|
|
|
|
|
|
## Build
|
|
For build instructions, please see the [BUILD page](../build/eps.md#amd-rocm).
|
|
|
|
## Usage
|
|
|
|
### C/C++
|
|
|
|
```c++
|
|
Ort::Env env = Ort::Env{ORT_LOGGING_LEVEL_ERROR, "Default"};
|
|
Ort::SessionOptions so;
|
|
int device_id = 0;
|
|
Ort::ThrowOnError(OrtSessionOptionsAppendExecutionProvider_ROCm(so, device_id));
|
|
```
|
|
|
|
The C API details are [here](../get-started/with-c.md).
|
|
|
|
### Python
|
|
Python APIs details are [here](https://onnxruntime.ai/docs/api/python/api_summary.html).
|
|
|
|
## Performance Tuning
|
|
For performance tuning, please see guidance on this page: [ONNX Runtime Perf Tuning](../performance/tune-performance.md)
|
|
|
|
## Samples
|
|
|
|
### Python
|
|
|
|
```python
|
|
import onnxruntime as ort
|
|
|
|
model_path = '<path to model>'
|
|
|
|
providers = [
|
|
'ROCmExecutionProvider',
|
|
'CPUExecutionProvider',
|
|
]
|
|
|
|
session = ort.InferenceSession(model_path, providers=providers)
|
|
```
|