Installation.md

Installation

We suggest to install or use the package in the Python virtual environment.

If you want to optimize a model from PyTorch, install PyTorch by following PyTorch installation guide. For other backend follow: TensorFlow installation guide, ONNX installation guide, OpenVINO installation guide.

As a PyPI package:

NNCF can be installed as a regular PyPI package via pip:

pip install nncf

If you want to install both NNCF and the supported PyTorch version in one line, you can do this by simply running:

pip install nncf[torch]

Other viable options besides [torch] are [tf], [onnx] and [openvino].

As a package built from a checked-out repository:

Install the package and its dependencies by running the following command in the repository root directory:

pip install .

Use the same pip install syntax as above to install NNCF along with the backend package version in one go:

pip install .[<BACKEND>]

List of supported backends: torch, tf, onnx and openvino.

For development purposes install extra packages by

pip install .[dev,tests]

NB: For launching example scripts in this repository, we recommend setting the PYTHONPATH variable to the root of the checked-out repository once the installation is completed.

NNCF is also available via conda:

conda install -c conda-forge nncf

From a specific commit hash using pip:

pip install git+https://github.com/openvinotoolkit/nncf@bd189e2#egg=nncf

Note that in order for this to work for pip versions >= 21.3, your Git version must be at least 2.22.

As a Docker image

Use one of the Dockerfiles in the docker directory to build an image with an environment already set up and ready for running NNCF sample scripts.