Installation

Depending on your OS, Concrete-ML may be installed with Docker or with pip:

Also, only some versions of python are supported: in the current release, these are 3.7 (linux only), 3.8 and 3.9.

Most of these limits are shared with the rest of the Concrete stack (namely Concrete-Numpy and Concrete-Compiler). Support for more platforms will be added in the future.

Using PyPi

Requirements

Installing Concrete-ML using PyPi requires a Linux-based OS or macOS running on an x86 CPU. For Apple Silicon, Docker is the only currently supported option (see below).

Installing on Windows can be done using Docker or WSL. On WSL, Concrete-ML will work as long as the package is not installed in the /mnt/c/ directory, which corresponds to the host OS filesystem.

Installation

To install Concrete-ML from PyPi, run the following:

pip install -U pip wheel setuptools
pip install concrete-ml

This will automatically install all dependencies, notably Concrete-Numpy.

Using Docker

Concrete-ML can be installed using Docker by either pulling the latest image or a specific version:

docker pull zamafhe/concrete-ml:latest
# or
docker pull zamafhe/concrete-ml:v0.4.0

The image can be used with Docker volumes, see the Docker documentation here.

The image can then be used via the following command:

# Without local volume:
docker run --rm -it -p 8888:8888 zamafhe/concrete-ml

# With local volume to save notebooks on host:
docker run --rm -it -p 8888:8888 -v /host/path:/data zamafhe/concrete-ml

This will launch a Concrete-ML enabled Jupyter server in Docker that can be accessed directly from a browser.

Alternatively, a shell can be lauched in Docker, with or without volumes:

docker run --rm -it zamafhe/concrete-ml /bin/bash