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Quick-start Docker containers for ONNX Runtime

nGraph Version (Preview)

Linux 16.04, Python Bindings

  1. Build the docker image from the Dockerfile in this repository.
# If you have a Linux machine, preface this command with "sudo"

docker build -t onnxruntime-ngraph -f Dockerfile.ngraph .
  1. Run the Docker image
# If you have a Linux machine, preface this command with "sudo"

docker run -it onnxruntime-ngraph

ONNX Runtime Server (Preview)

Linux 16.04

  1. Build the docker image from the Dockerfile in this repository
docker build -t {docker_image_name} -f Dockerfile.server .
  1. Run the ONNXRuntime server with the image created in step 1
docker run -v {localModelAbsoluteFolder}:{dockerModelAbsoluteFolder} -e MODEL_ABSOLUTE_PATH={dockerModelAbsolutePath} -p {your_local_port}:8001 {imageName}
  1. Send HTTP requests to the container running ONNX Runtime Server

Send HTTP requests to the docker container through the binding local port. Here is the full usage document.

curl  -X POST -d "@request.json" -H "Content-Type: application/json" http://0.0.0.0:{your_local_port}/v1/models/mymodel/versions/3:predict  

OpenVINO Version (Preview)

Linux 16.04, Python Bindings

  1. Build the docker image from the Dockerfile in this repository.
# If you have a Linux machine, preface this command with "sudo"

docker build -t onnxruntime-openvino -f Dockerfile.openvino .

To use GPU_FP32:

docker build -t onnxruntime-openvino --build-arg TARGET_DEVICE=GPU_FP32 -f Dockerfile.openvino .
  1. Run the Docker image
# If you have a Linux machine, preface this command with "sudo"

docker run -it onnxruntime-openvino