diff --git a/docs/Installation-Windows.md b/docs/Installation-Windows.md index 43d705116e..646c36ef48 100644 --- a/docs/Installation-Windows.md +++ b/docs/Installation-Windows.md @@ -7,8 +7,8 @@ Windows VM such as Bootcamp or Parallels. To use the ML-Agents toolkit, you install Python and the required Python packages as outlined below. This guide also covers how set up GPU-based training -(for advanced users). GPU-based training is not required for the v0.4 release of -the ML-Agents toolkit. However, training on a GPU might be required by future +(for advanced users). GPU-based training is not currently required for the +ML-Agents toolkit. However, training on a GPU might be required by future versions and features. ## Step 1: Install Python via Anaconda @@ -126,19 +126,28 @@ git clone https://github.com/Unity-Technologies/ml-agents.git If you don't want to use Git, you can always directly download all the files [here](https://github.com/Unity-Technologies/ml-agents/archive/master.zip). +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. + +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. + In our example, the files are located in `C:\Downloads`. After you have either -cloned or downloaded the files, from the Anaconda Prompt, change to the python -directory inside the ml-agents directory: +cloned or downloaded the files, from the Anaconda Prompt, change to the ml-agents +subdirectory inside the ml-agents directory: ```console cd C:\Downloads\ml-agents\ml-agents ``` Make sure you are connected to the internet and then type in the Anaconda -Prompt: +Prompt within `ml-agents` subdirectory: ```sh -pip install . +pip install -e . ``` This will complete the installation of all the required Python packages to run @@ -152,7 +161,7 @@ GPU). This is a guide for advanced users who want to train using GPUs. Additionally, you will need to check if your GPU is CUDA compatible. Please check Nvidia's page [here](https://developer.nvidia.com/cuda-gpus). -As of the ML-Agents toolkit v0.4, only CUDA v9.0 and cuDNN v7.0.5 is supported. +Currently for the ML-Agents toolkit, only CUDA v9.0 and cuDNN v7.0.5 is supported. ### Install Nvidia CUDA toolkit diff --git a/docs/Installation.md b/docs/Installation.md index eb3d779afc..ebf82ebdb7 100644 --- a/docs/Installation.md +++ b/docs/Installation.md @@ -16,7 +16,14 @@ Build Support_ component when installing Unity. width="500" border="10" />

-## Clone the ML-Agents Toolkit Repository +## Windows Users +For setting up your environment on Windows, we have created a [detailed +guide](Installation-Windows.md) 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. @@ -26,14 +33,14 @@ 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](Learning-Environment-Examples.md) -that can be used to help get you familiar with Unity. +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 +### Install Python and mlagents Package In order to use ML-Agents toolkit, you need Python 3.6 along with the dependencies listed in the [requirements file](../ml-agents/requirements.txt). @@ -42,21 +49,6 @@ Some of the primary dependencies include: - [TensorFlow](Background-TensorFlow.md) - [Jupyter](Background-Jupyter.md) -### 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 - [note](https://www.tensorflow.org/install/install_mac#installing_with_anaconda) - on how to install TensorFlow in an Anaconda environment. - -### Windows Users - -If you are a Windows user who is new to Python and TensorFlow, follow [this -guide](Installation-Windows.md) to set up your Python environment. - -### Mac and Unix Users - [Download](https://www.python.org/downloads/) and install Python 3.6 if you do not already have it. @@ -68,12 +60,20 @@ To install the dependencies and `mlagents` Python package, enter the `ml-agents/` subdirectory and run from the command line: ```sh -pip3 install . +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 + [note](https://www.tensorflow.org/install/install_mac#installing_with_anaconda) + on how to install TensorFlow in an Anaconda environment. + ## Docker-based Installation If you'd like to use Docker for ML-Agents, please follow diff --git a/docs/Migrating.md b/docs/Migrating.md index 9e2406f904..d82565e8e8 100644 --- a/docs/Migrating.md +++ b/docs/Migrating.md @@ -54,13 +54,14 @@ using the search bar of the `Hierarchy` window with the word `Agent`. python3 learn.py 3DBall --train ``` - from the `python/` directory, we now run + from the `python` subdirectory (which is changed to `ml-agents` subdirectory + in v0.5), we now run ```sh mlagents-learn config/trainer_config.yaml --env=3DBall --train ``` - from the directory where we installed the ML-Agents Toolkit. + from the root directory where we installed the ML-Agents Toolkit. * It is now required to specify the path to the yaml trainer configuration file when running `mlagents-learn`. For an example trainer configuration file, see @@ -88,7 +89,8 @@ using the search bar of the `Hierarchy` window with the word `Agent`. ### Python API * We've changed some of the Python packages dependencies in requirement.txt - file. Make sure to run `pip3 install .` within your `ml-agents/python` folder + file. Make sure to run `pip3 install -e .` within your `ml-agents/python` + folder to update your Python packages. ## Migrating from ML-Agents toolkit v0.2 to v0.3 diff --git a/docs/Training-on-Amazon-Web-Service.md b/docs/Training-on-Amazon-Web-Service.md index 49280fbccc..2f564c7a93 100644 --- a/docs/Training-on-Amazon-Web-Service.md +++ b/docs/Training-on-Amazon-Web-Service.md @@ -66,7 +66,7 @@ After launching your EC2 instance using the ami and ssh into it: ```sh git clone https://github.com/Unity-Technologies/ml-agents.git cd ml-agents/ml-agents/ - pip3 install . + pip3 install -e . ``` ### Setting up X Server (optional)