Installation

The following setup was tested with the following system configuration:

• Ubuntu 18.04.2 LTS

• CUDA 10.1 (driver version 418.87.00)

• Anaconda (Python 3.7.6)

• PyTorch 1.4

In the following, we assume that we work in /tmp (obviously, you have to change this to reflect your choice and using /tmp is, of course, not the best choice :).

First, get the Anaconda installer and install Anaconda (in /tmp/anaconda3) using

cd /tmp/
wget https://repo.anaconda.com/archive/Anaconda3-2019.10-Linux-x86_64.sh
bash Anaconda3-2019.10-Linux-x86_64.sh
# specify /tmp/anaconda3 as your installation path
source /tmp/anaconda3/bin/activate

Second, we install PyTorch (v1.4) using

conda install pytorch torchvision cudatoolkit=10.1 -c pytorch

Third, we clone the torchph repository from GitHub and make it available within Anaconda.

cd /tmp/
git clone https://github.com/c-hofer/torchph.git
conda develop /tmp/torchph

A quick check if everything works can be done with

>>> import torchph

Note

At the moment, we only have GPU support available. CPU support is not planned yet, as many other packages exist which support PH computation on the CPU.