Installation

This package works with Python 3.6 through 3.8 in Linux, Mac and Windows.

You can install the latest stable version of this library directly from PyPI using PIP:

$ pip install d3m-interface

AutoML systems via containers

For this option, you need to have Docker or Singularity installed on your operating system.

Everything you need to deploy, d3m-interface will simply run on the Docker/Singularity engine as a container. You can see here how this container is set up to deploy different AutoML systems.

Note that d3m-interface uses the pre-built Docker images of the D3M AutoML systems. For AlphaD3M, you can see here how the Docker image is built. For the other D3M AutoML systems, you can find more information here.

Once the installation is completed, you need to pull manually the Docker image of the D3M AutoML system.

For AlphaD3M run:

$ # for docker
$ docker pull registry.gitlab.com/vida-nyu/d3m/alphad3m:latest

or

$ # for singularity
$ singularity pull docker://registry.gitlab.com/vida-nyu/d3m/alphad3m:latest

AutoML systems via PyPI

For this option, you don’t need to install neither Docker nor Singularity. Once the installation of d3m-interface is completed, you need to install the PyPI version of the AutoML system and primitives.

For AlphaD3M run:

$ pip install alphad3m

To install the primitives available on PyPI, run this command:

$ pip install d3m-common-primitives d3m-sklearn-wrap dsbox-corex dsbox-primitives sri-d3m distil-primitives d3m-esrnn d3m-nbeats --no-binary pmdarima

Currently, this version has support for classification, regression and forecasting tasks (using a limited set of primitives). It supports tabular, text and image data types. This package works with Python 3.8 in Linux and Mac.

On non-Linux platforms, you will need swig to compile pyrfr. You can obtain swig from homebrew, anaconda, or the swig website.