Welcome to the Engine Documentation. Engine allows you to easily track and execute machine learning code. In this guide, we will walk you through creating an account and launching your first run.
Create an Account
In order to interact with Engine, create an account and set up your machine.
Install the CLI and Library
Use the following
pip install command to install the Engine command line interface and python library. We recommend
using a fresh virtual environment.
$ pip install --upgrade -i https://pypi.app.engineml.com/simple engineml-cli engineml
Set up Autocomplete
After you've installed the pip packages, enable autocomplete on the CLI. Autocomplete will allow you to tab-complete
engine commands on your terminal.
$ engine autocomplete > ~/.engine/autocomplete$ echo "source ~/.engine/autocomplete" >> ~/.bashrc
Add an SSH Key
Engine operates services that communicate over ssh. These services are secured via the use of ssh keys. If you do not have a public/private key pair, generate one:
$ ssh-keygen -t rsa -b 4096 -C "email@example.com"Generating public/private rsa key pair.Enter file in which to save the key (~/.ssh/id_rsa):Enter passphrase (empty for no passphrase):Enter same passphrase again:
Copy the public key contents with your favorite text editor or with
pbcopy < ~/.ssh/id_rsa.pub. Paste the contents
into the "Add SSH Key" modal on your settings page.
Generate an API Key
Use your new API key to log into Engine on your terminal with
engine login. If you have
not already added an ssh key to your account, you will be prompted to do so during the login process.
$ engine login 'API_KEY'Welcome firstname.lastname@example.org!
Launch a Run
Now that you have initialized your account, we can launch our first run.
Create a Project
Open the dashboard and create a new project called quickstart.
Engine ML hosts examples for training MNIST on GitHub
$ git clone email@example.com:EngineML/Examples.git$ cd Examples
Engine uses run configurations to know how to execute your code. The
--override flag of
engine run automatically
repository field in your run configuration.
$ bash get-data.sh$ pip install -r tf/mnist/requirements.txt$ engine run tf/mnist/local.yaml -o repository owner/quickstart