Microsoft.ML.OnnxRuntime.Gpu.Linux 1.20.1

About

ONNX Runtime is a cross-platform machine-learning inferencing accelerator.

ONNX Runtime can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms.

Learn more → here

NuGet Packages

ONNX Runtime Native packages

Microsoft.ML.OnnxRuntime

• Native libraries for all supported platforms
• CPU Execution Provider
• CoreML Execution Provider on macOS/iOS
  • https://onnxruntime.ai/docs/execution-providers/CoreML-ExecutionProvider.html
• XNNPACK Execution Provider on Android/iOS
  • https://onnxruntime.ai/docs/execution-providers/Xnnpack-ExecutionProvider.html

Microsoft.ML.OnnxRuntime.Gpu

• Windows and Linux
• TensorRT Execution Provider
  • https://onnxruntime.ai/docs/execution-providers/TensorRT-ExecutionProvider.html
• CUDA Execution Provider
  • https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html
• CPU Execution Provider

Microsoft.ML.OnnxRuntime.DirectML

• Windows
• DirectML Execution Provider
  • https://onnxruntime.ai/docs/execution-providers/DirectML-ExecutionProvider.html
• CPU Execution Provider

Microsoft.ML.OnnxRuntime.QNN

• 64-bit Windows
• QNN Execution Provider
  • https://onnxruntime.ai/docs/execution-providers/QNN-ExecutionProvider.html
• CPU Execution Provider

Other packages

Microsoft.ML.OnnxRuntime.Managed

• C# language bindings

Microsoft.ML.OnnxRuntime.Extensions

• Custom operators for pre/post processing on all supported platforms.
  • https://github.com/microsoft/onnxruntime-extensions