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5601b10644
-Add MIGraphX-EP page for install/example -Update version info for ROCm version for both MIGraphx and ROCm EPs to 5.4 -Update hooks to the latest ROCm Pytorch supported (1.12.1 -> 1.13) -Remove (Preview) from MIGraphx and ROCm EP notes -Update ROCm & MIGraphX EP.md files with ROCm version and pytorch links ### Description <!-- Describe your changes. --> Update documentation about ROCm and MIGraphx with newest ROCm 5.4 stack ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. --> Update things for whats able to be supported. Co-authored-by: Ted Themistokleous <tthemist@amd.com>
77 lines
1.8 KiB
Markdown
77 lines
1.8 KiB
Markdown
---
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title: AMD - ROCm
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description: Instructions to execute ONNX Runtime with the AMD ROCm execution provider
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parent: Execution Providers
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nav_order: 10
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redirect_from: /docs/reference/execution-providers/ROCm-ExecutionProvider
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---
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# ROCm Execution Provider
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{: .no_toc }
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The ROCm Execution Provider enables hardware accelerated computation on AMD ROCm-enabled GPUs.
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## Contents
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{: .no_toc }
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* TOC placeholder
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{:toc}
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## Install
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**NOTE** Please make sure to install the proper version of Pytorch specified here [PyTorch Version](../install/#training-install-table-for-all-languages).
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For Nightly PyTorch builds please see [Pytorch home](https://pytorch.org/) and select ROCm as the Compute Platform.
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Pre-built binaries of ONNX Runtime with ROCm EP are published for most language bindings. Please reference [Install ORT](../install).
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## Requirements
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|ONNX Runtime|ROCm|
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|---|---|
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|main|5.4|
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|1.13|5.4|
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|1.13|5.3.2|
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|1.12|5.2.3|
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|1.12|5.2|
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## Build
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For build instructions, please see the [BUILD page](../build/eps.md#amd-rocm).
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## Usage
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### C/C++
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```c++
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Ort::Env env = Ort::Env{ORT_LOGGING_LEVEL_ERROR, "Default"};
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Ort::SessionOptions so;
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int device_id = 0;
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Ort::ThrowOnError(OrtSessionOptionsAppendExecutionProvider_ROCm(so, device_id));
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```
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The C API details are [here](../get-started/with-c.md).
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### Python
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Python APIs details are [here](https://onnxruntime.ai/docs/api/python/api_summary.html).
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## Performance Tuning
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For performance tuning, please see guidance on this page: [ONNX Runtime Perf Tuning](../performance/tune-performance.md)
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## Samples
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### Python
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```python
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import onnxruntime as ort
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model_path = '<path to model>'
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providers = [
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'ROCmExecutionProvider',
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'CPUExecutionProvider',
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]
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session = ort.InferenceSession(model_path, providers=providers)
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```
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