Installation
Please note that not all hardware/OS combinations are supported. Determine your platform, OS version and Python version before referencing the table below.
Depending on your OS, Concrete-ML may be installed with Docker or with pip:
OS / HW | Available on Docker | Available on pip |
---|---|---|
Linux | Yes | Yes |
Windows | Yes | Not currently |
Windows Subsystem for Linux | Yes | Yes |
macOS (Intel) | Yes | Yes |
macOS (Apple Silicon, ie M1, M2 etc) | Yes | Not currently |
Also, only some versions of python
are supported: in the current release, these are 3.8
and 3.9
. Please note that, at the time of this Concrete-ML version release, Kaggle or Google Colab use Python 3.7 which is a deprecated version and is not supported by Concrete-ML.
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:
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:
The image can be used with Docker volumes, see the Docker documentation here.
The image can then be used via the following command:
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:
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