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The torch-ort packages uses the PyTorch APIs to accelerate PyTorch models using ONNX Runtime.

Dependencies

The torch-ort package depends on the onnxruntime-training package, which depends on specific versions of GPU libraries such as NVIDIA CUDA.

The default command pip install torch-ort installs the onnxruntime-training version that depends on CUDA 10.2.

If you have a different version of CUDA installed, you can install a different version of onnxruntime-training explicitly:

CUDA 11.1 pip install onnxruntime-training -f https://download.onnxruntime.ai/onnxruntime_stable_cu111.html

Post-installation step

Once torch-ort is installed, there is a post-installation step:

python -m torch_ort.configure

If this step fails, it is likely due to GPU library version mismatch between onnxruntime-training and your installation. You can check the version of onnxruntime-training by running pip list. For example:

onnxruntime-training 1.9.0+cu111

Releases

1.9.0

Release Notes : https://github.com/pytorch/ort/releases/tag/v1.9.0
1.8.1

Release Notes : https://github.com/pytorch/ort/releases/tag/v1.8.1

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Dependencies of torch-ort (2).
Dependency	Optional
onnxruntime-training	false
torch	false

Package profile

torch-ort

Releases

Release table

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Details

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Dependencies

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