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Installation Guide
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NVIDIA CUDA GPU: Compute Capability of the GPU must be at least 3.0.
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CUDA Toolkit: Supported Versions: 8.0, 9.0, 9.1, 9.2, 10.0, and 10.1.
(Note: Qualia2.0 can be used without GPU)
Ubuntu is recommended for the installation environment. Some packages fail to build on Windows.
Upgrade of setuptools and pip is recommended before the installation:
$ pip install -U setuptools pip
CUDA Toolkit version can be found by:
$ nvcc --version
Depending on the CUDA version you have installed on your host, choose the best option from following.
(For CUDA 8.0)
$ python setup.py install --cuda 80
(For CUDA 9.0)
$ python setup.py install --cuda 90
(For CUDA 9.1)
$ python setup.py install --cuda 91
(For CUDA 9.2)
$ python setup.py install --cuda 92
(For CUDA 10.0)
$ python setup.py install --cuda 100
(For CUDA 10.1)
% python setup.py install --cuda 101
(For without CUDA)
$ python setup.py install
For the installation on windows, there might be some error during the installation.
Here are some wheel files that might help:
The way to install from wheel is:
Note that you do need to install the wheel package first:
$ pip install wheelThen,
$ pip install /path/to/the/wheel_file.whl
For several challenging continuous control environments, OpenAI gym requires the user to install MuJoCo, a commercial physics engine which requires a license to run for longer than 30 days. Here are two options:
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Obtain a 30-day free trial on the MuJoCo website or free license if you are a student. The license key will arrive in an email with your username and password.
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Download the MuJoCo version 2.0 binaries.
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Unzip the downloaded
mujoco200
directory into~/.mujoco/mujoco200
, and place your license key (themjkey.txt
file from your email) at~/.mujoco/mjkey.txt
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Install mujoco-py
$ git clone https://github.com/openai/mujoco-py.git
$ cd mujoco-py
$ pip install -r requirements.txt
$ pip install -r requirements.dev.txt
$ python setup.py install
- To run
mujoco-py
, MuJoCo needs to be installed on the machine. - For windows, install Microsoft Visual C++ Build Tools 2015 with Windows 8.1 SDK and Windows 10 SDK options
I highly recommend PyBullet as a free open source alternative to MuJoCo for continuous control tasks.
PyBullet Gymperium is an open-source implementation of the OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform in support of open research.
git clone https://github.com/benelot/pybullet-gym.git
cd pybullet-gym
pip install -e .