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Installation
To install and use ML-Agents, you need to install Unity, clone this repository and install Python with additional dependencies. Each of the subsections below overviews each step, in addition to a Docker set-up.
Install Unity 2017.4 or Later
Download and install Unity. If you would like to use our Docker set-up (introduced later), make sure to select the Linux Build Support component when installing Unity.
Windows Users
For setting up your environment on Windows, we have created a detailed guide to setting up your env. For Mac and Linux, continue with this guide.
Mac and Unix Users
Clone the ML-Agents Toolkit Repository
Once installed, you will want to clone the ML-Agents Toolkit GitHub repository.
git clone https://github.com/Unity-Technologies/ml-agents.git
The UnitySDK subdirectory contains the Unity Assets to add to your projects.
It also contains many example environments
to help you get started.
The ml-agents subdirectory contains Python packages which provide
trainers and a Python API to interface with Unity.
The gym-unity subdirectory contains a package to interface with OpenAI Gym.
Install Python and mlagents Package
In order to use ML-Agents toolkit, you need Python 3.6 along with the dependencies listed in the setup.py file. Some of the primary dependencies include:
- TensorFlow (Requires a CPU w/ AVX support)
- Jupyter
Download and install Python 3.6 if you do not already have it.
If your Python environment doesn't include pip3, see these
instructions
on installing it.
To install the dependencies and mlagents Python package, enter the
ml-agents/ subdirectory and run from the command line:
pip3 install -e .
If you installed this correctly, you should be able to run
mlagents-learn --help
Notes:
- We do not currently support Python 3.7 or Python 3.5.
- If you are using Anaconda and are having trouble with TensorFlow, please see the following link on how to install TensorFlow in an Anaconda environment.
Docker-based Installation
If you'd like to use Docker for ML-Agents, please follow this guide.
Next Steps
The Basic Guide page contains several short tutorials on setting up the ML-Agents toolkit within Unity, running a pre-trained model, in addition to building and training environments.
Help
If you run into any problems regarding ML-Agents, refer to our FAQ and our Limitations pages. If you can't find anything please submit an issue and make sure to cite relevant information on OS, Python version, and exact error message (whenever possible).