Installation¶

Basic installation is simple:

pip install nnio

To use one of backends, additional installs are needed:

ONNX¶

To work with onnx backend, install onnxruntime package:

pip install onnxruntime

EdgeTPU¶

To work with EdgeTPU models, tflite_runtime is required. See the installation guide: https://www.tensorflow.org/lite/guide/python.

If you intend to only use CPU inference, tensorflow installation will be enough.

OpenVINO¶

To work with OpenVINO models user needs to install openvino package. The easiest way to do it is to use openvino/ubuntu18_runtime docker. The following command allows to pass all Myriad and GPU devices into docker container:

docker run -itu root:root --rm \
-v /var/tmp:/var/tmp \
--device /dev/dri:/dev/dri --device-cgroup-rule='c 189:* rmw' \
-v /dev/bus/usb:/dev/bus/usb \
-v /etc/timezone:/etc/timezone:ro \
-v /etc/localtime:/etc/localtime:ro \
-v "$(pwd):/input" openvino/ubuntu18_runtime

Torch¶

To work with saved torch models, torch package needs to be installed. It weights around 0.8 GB, hense it is recommended to use other backends instead.

To install torch:

pip3 install torch