Currently, CubeAI has two distinct development ports; Python port and C++ port. Below are instructions how to install either or both. One of the future goals is to merge these two ports.

Python installation

PyCubeAI depends on several packages. Specifically, the following packages are required:

pip install -r requirements.txt

Execute tests

C++ installation

The C++ port of CubeAI has the following dependencies

If you choose PyTorch with CUDA then `cuDNN` library is also required. This is a runtime library containing primitives for deep neural networks.

Furthermore, CubeAI has the following integrated dependencies

Installation then follows the usual steps

mkdir build && cd build
cmake ..
make install

If you are using `rl_envs_from_cpp` you need to export the path to the Python version you are using. For ecample:

export CPLUS_INCLUDE_PATH="$CPLUS_INCLUDE_PATH:/usr/include/python3.8/"


export CPLUS_INCLUDE_PATH="$CPLUS_INCLUDE_PATH:/usr/include/python3.10/"

Depending on the values of the `CMAKE_BUILD_TYPE`, the produced shared library will be installed in `CMAKE_INSTALL_PREFIX/dbg/` or `CMAKE_INSTALL_PREFIX/opt/` directories.

Issues with C++ installation

  • Could not find boost. On a Ubuntu machine you can install the boost libraries as follows

` sudo apt-get install libboost-dev `

  • pyconfig.h not found

In this case we may have to export the path to your Python library directory as shown above.

  • Problems with Blaze includes

cubeai is using Blaze-3.8. As of this version the FIND_PACKAGE( blaze ) command does not populate BLAZE_INCLUDE_DIRS therefore you manually have to set the variable appropriately for your system. So edit the project’s CMakeLists.txt file and populate appropriately the variable BLAZE_INCLUDE_DIRS.

  • Could NOT find BLAS

The `Blaze` library depends on BLAS so it has to be installed. On a Ubuntu machine this can be doe as follows

` sudo apt-get install libblas-dev liblapack-dev `

Generate documentation

You will need Sphinx in order to generate the API documentation. Assuming that Sphinx is already installed on your machine execute the following commands (see also Sphinx tutorial).

sphinx-quickstart docs
sphinx-build -b html docs/source/ docs/build/html