installation.rst

Installation

Requirements

• CUDA 10.2 supported GPU.
• Linux with Python ≥ 3.8
• PyTorch ≥ 1.6

Install using Docker

We provide a Dockerfile which install DIRECT with a few commands. While recommended due to the use of specific pytorch features, DIRECT should also work in a virtual environment.

Install using conda

1. First, install conda. Here is a guide on how to install conda on Linux if you don't already have it here. If you downloaded conda for the first time it is possible that you will need to restart your machine. Once you have conda, create a python 3.9 conda environment:

   conda create -n myenv python=3.9
   

   Then, activate the virtual environment myenv you created where you will install the software:

   conda activate myenv
   

2. If you are using GPUs, cuda is required for the project to run. To install PyTorch with cuda run:

   pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
   

   otherwise, install the CPU PyTorch installation (not recommended):

   pip3 install torch==1.10.0+cpu torchvision==0.11.1+cpu torchaudio==0.10.0+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
   

3. Clone the repository using git clone and navigate to direct/direct/ and run

   python3 setup.py install
   

   This will install direct as a python module.

Common Installation Issues

If you met issues using DIRECT, please first update the repository to the latest version, and rebuild the docker. When this does not work, create a GitHub issue so we can see whether this is a bug, or an installation problem.