# 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](https://store.unity.com/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.

Linux Build Support

## Environment Setup We now support a single mechanism for installing ML-Agents on Mac/Windows/Linux using Virtual Environments. For more information on Virtual Environments and installation instructions, follow this [guide](Using-Virtual-Environment.md). Although we don't support Anaconda installation path of ML-Agents for Windows, the previous guide is still in the docs folder. Please refer to [Windows Installation (Deprecated)](Installation-Windows.md). ### Clone the ML-Agents Toolkit Repository Once installed, you will want to clone the ML-Agents Toolkit GitHub repository. ```sh git clone --branch latest_release https://github.com/Unity-Technologies/ml-agents.git ``` The `--branch latest_release` option will switch to the tag of the latest stable release. Omitting that will get the `master` branch which is potentially unstable. The `UnitySDK` subdirectory contains the Unity Assets to add to your projects. It also contains many [example environments](Learning-Environment-Examples.md) to help you get started. ### Package Installation If you intend to copy the `UnitySDK` folder in to your project, ensure that you have the [Barracuda preview package](https://docs.unity3d.com/Packages/com.unity.barracuda@0.3/manual/index.html) installed. To install the Barracuda package in Unity **2017.4.x**, you will have to copy the `UnityPackageManager` folder under the `UnitySDK` folder to the root directory of your project. To install the Barrcuda package in later versions of Unity, navigate to the Package Manager window by navigating to the menu `Window` -> `Package Manager`. Click on the `Adavanced` dropdown menu to the left of the search bar and make sure "Show Preview Packages" is checked. Search for or select the `Barracuda` package and install the latest version.

Barracuda Package Manager

The `ml-agents` subdirectory contains a Python package which provides deep reinforcement learning trainers to use with Unity environments. The `ml-agents-envs` subdirectory contains a Python API to interface with Unity, which the `ml-agents` package depends on. 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 3.6.1 or higher. [Download](https://www.python.org/downloads/) and install the latest version of Python if you do not already have it. If your Python environment doesn't include `pip3`, see these [instructions](https://packaging.python.org/guides/installing-using-linux-tools/#installing-pip-setuptools-wheel-with-linux-package-managers) on installing it. To install the `mlagents` Python package, run from the command line: ```sh pip3 install mlagents ``` Note that this will install `ml-agents` from PyPi, _not_ from the cloned repo. If you installed this correctly, you should be able to run `mlagents-learn --help`, after which you will see the Unity logo and the command line parameters you can use with `mlagents-learn`. By installing the `mlagents` package, the dependencies listed in the [setup.py file](../ml-agents/setup.py) are also installed. Some of the primary dependencies include: - [TensorFlow](Background-TensorFlow.md) (Requires a CPU w/ AVX support) - [Jupyter](Background-Jupyter.md) **Notes:** - We do not currently support Python 3.5 or lower. - If you are using Anaconda and are having trouble with TensorFlow, please see the following [link](https://www.tensorflow.org/install/pip) on how to install TensorFlow in an Anaconda environment. ### Installing for Development If you intend to make modifications to `ml-agents` or `ml-agents-envs`, you should install the packages from the cloned repo rather than from PyPi. To do this, you will need to install `ml-agents` and `ml-agents-envs` separately. From the repo's root directory, run: ```sh cd ml-agents-envs pip3 install -e ./ cd .. cd ml-agents pip3 install -e ./ ``` Running pip with the `-e` flag will let you make changes to the Python files directly and have those reflected when you run `mlagents-learn`. It is important to install these packages in this order as the `mlagents` package depends on `mlagents_envs`, and installing it in the other order will download `mlagents_envs` from PyPi. ## Next Steps The [Basic Guide](Basic-Guide.md) 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](FAQ.md) and our [Limitations](Limitations.md) pages. If you can't find anything please [submit an issue](https://github.com/Unity-Technologies/ml-agents/issues) and make sure to cite relevant information on OS, Python version, and exact error message (whenever possible).