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How to Change Model Inference Backend
FastDeploy supports various backends, including
- OpenVINO (supports Paddle/ONNX formats, CPU inference only )
- ONNX Runtime (supports Paddle/ONNX formats, inference on CPU/GPU)
- TensorRT (supports Paddle/ONNX formats, GPU inference only)
- Paddle Inference (supports Paddle format, inference on CPU/GPU)
All models can backend via RuntimeOption
Python
import fastdeploy as fd
option = fd.RuntimeOption()
# Change CPU/GPU
option.use_cpu()
option.use_gpu()
# Change the Backend
option.use_paddle_backend() # Paddle Inference
option.use_trt_backend() # TensorRT
option.use_openvino_backend() # OpenVINO
option.use_ort_backend() # ONNX Runtime
C++
fastdeploy::RuntimeOption option;
// Change CPU/GPU
option.UseCpu();
option.UseGpu();
// Change the Backend
option.UsePaddleBackend(); // Paddle Inference
option.UseTrtBackend(); // TensorRT
option.UseOpenVINOBackend(); // OpenVINO
option.UseOrtBackend(); // ONNX Runtime
For more specific demos, please refer to python or c++ inference code for different models under FastDeploy/examples/vision
For more deployment methods, please refer to FastDeploy API tutorials.